2.4 Evaluation and development of the exploration

2.4.1 Integrated interpretation,geological modelling

Integration of seismic and geologicalinterpretations

Exploration for hydrocarbons trapped undergroundpresupposes the simultaneous presence of twoelements: a trap and hydrocarbons. The first elementcorresponds to the geometric component that isobtained from the interpretation of geophysical, and inparticular seismic, measurements. The second elementis the fluid component, obtained sometimes fromseismic indicators (direct hydrocarbon indicators) andin the majority of cases from geological modelling.

To obtain an image of the subsoil useful forunderstanding the field’s geometry we mainly useindirect measurements (seismic reflections) and veryfew direct measurements (well data). In practice, the indirect measurements must be inverted in orderto obtain the geological model that produced them.This operation requires different and complexprocessing phases of the seismic signal; its weakpoints are in the interpretation of the seismicreflections and the evaluation of the field of propagation velocities of the seismic signal. Both these elements introduce a degree of uncertaintyin the evaluation of the trap geometry. Interpretation is essential for the exploration phase becauseit adds the geological information that is only partiallypresent in the data and thus leans on a conceptualmodel. As different conceptual models give riseto different interpretations of the same seismic data,it is fundamental to obtain the greatest quantity ofgeological information on an area, so as to build theconceptual model of the area as accurately as possibleand define just a few probable scenarios tied to thevarious conceptual models and differentinterpretations. The uncertainty in the interpretation of

seismic data represents the greatest source of‘geometric risk’ in the evaluation of a possibleprospect; it is thus advisable not to exclude anyalternative scenarios, but to keep and treat them inparallel. Seismic velocities are indirectly obtained byexploiting the multiplicity of the reflections (multiplecoverage) for every point identified by the seismicenergy in the acquisition process. This involves aninversion process of the seismic data, which studiesthe coherence of all the seismic signals, with the samereflection point. To make an analogy, it is likechanging the properties (the propagation velocity) ofthe underground lens until the seismic image becomessharp. This process is repeated for different points ofevery underground interface that gives rise to seismicreflections, so as to obtain a three-dimensionalvelocity field. Due to the limitations in the resolutionpower of seismic signals, several three-dimensionalvelocity fields are compatible with the measurementsavailable, and thus the geometric image of the trap issomewhat ‘fuzzy’, or rather there are variousevaluations on its spatial shape and position, allequally likely.

For every interpretation scenario multipledescriptions of the trap geometry are thus possible,due to the uncertainty of the seismic velocities. Forthis reason it is fundamental to integrate the geophysical data and the geological data (a seismic section in depth domain, a seismic intervalvelocities section, the geometries of the mostsignificant geological layers, the traces of drilled wells and also the temperature values calculated with thermo-tectonic studies; Fig. 1). The integration between the ‘views’ produced by the various investigation instruments helps to improve understanding of the subsoil model.

The fluid component, i.e. the presence ofhydrocarbons, must be evaluated by modelling all the

277VOLUME I / EXPLORATION, PRODUCTION AND TRANSPORT

2.4

Evaluation and developmentof the exploration

geological processes that have led to the accumulationof the hydrocarbons (see also Section 2.4.2); fromtheir generation in the source rock to migration intothe trap, including the preservation and/ordeterioration in the trap itself (Fig. 2). This involvesmodelling the entire geological evolution of the basinin which the potential traps are, paying particularattention to the processes that describe the evolutionof the oil system. The role of the conceptual model isessential, even more than in the case of seismicinterpretation, in that the information on the pasthistory of the basin is poor and has to be obtainedthrough measurements on the land, study of alreadyknown similar basin and analogue models. The role ofanalogue models is still a matter of debate betweenthe supporters of their direct use in trying toreproduce the particulars of a real geological basin indetail, and those who prefer to use them to clarify themore critical aspects of the conceptual model,reducing the basin to its essential elements. With this

second approach, the analogue modelling is integratedwith the geonumerical one, as it explains theinterpretive choices made during the geologicalmodelling itself (structural, sedimentological, oilsystem, etc.). Generally it involves inverting theavailable information to obtain the geologicalevolution of the modelled process and, in the finalanalysis, of the basin in question. It is, in fact, notpossible to describe mathematically and/ornumerically the inversion of a geological process (forexample hydrocarbons that return from the trap to thesource rock), because geological processes areabsolutely not linear or continuous (there existthreshold values above and below which a specificphenomenon occurs or does not) and their effects arecumulative in time. Thus it is only possible to producea direct numerical modelling of geological processes,i.e. of their evolution from the past to the present. Allthis further clarifies the fundamental role of theconceptual geological model, which must be sharedbetween the structural geologists, thesedimentological and the oil system geologists(including the geochemists). It also appears clear thatgeological modelling is essentially interpretive, in thatthe modeller does not know a priori the whole of themodel parameter values that will produce anacceptable result, but must find them through arepetitive process in which alternative conceptualhypotheses must be evaluated or discarded. Thisprocess can be made easier in various ways throughadvanced visualisations, partial optimisationtechniques or better still through sensitivity analysesthat highlight which parameters have a significant rolein the case in question. Interpretive geologicalmodelling thus produces different scenarioscompatible with the available measurements and

278 ENCYCLOPAEDIA OF HYDROCARBONS

PETROLEUM EXPLORATION

Fig. 1. Integration ofgeophysical andgeological data: seismicsection, velocities section,top of the explorationtarget with two structuraltraps highlighted, tracks ofdrilled wells, three levelsof the geological modelcoloured on the basis ofthe temperature calculatedfor these levels.

trap

hydrocarbons-water contact

migration paths

source

source

Fig. 2. Basin model section, highlighting the source levels (source rocks) of thehydrocarbons, the migration paths, and a trap in which hydrocarbons accumulate due to a permeability barrier.

information, corresponding to the different hypothesesadmissible for the conceptual geological model (Fig. 3).

It is important to underline again that theconceptual model is modified by the results ofgeological modelling because of the interpretivenature of the latter. This evolutionary nature of theconceptual geological model produces and requires thesharing of the basin’s geological model betweenmodellers of different disciplines. This conceptualmodel constitutes in concrete the first component ofthe Shared Earth Model at basin scale. The varioustypes of geological modelling are interdependent, asare natural geological processes; yet, for technicalreasons, they are applied in succession. One possibleworkflow could be the following:• Palaeobathymetric modelling: of kinematic

interpretive nature, it reconstructs the evolution ofthe basin’s bathymetry throughout geological time.

• Inverted structural modelling: of kinematicinterpretive nature, it evaluates the genesis of thepresent geometric model produced from seismicinterpretation, and produces an interpretation thatis in geological coherence with the fault system.

• Analogue modelling: it validates the main elementsof the conceptual geological model.

• Numerical structural modelling: of dynamicinterpretive nature; it confirms the coherence ofthe inverted structural modelling with the physicsof the process, and produces an evaluation of theforce field and the deformations associated withstructural evolution.

• Thermo-tectonic modelling: of dynamicinterpretive type, it produces an evaluation of theheat flow at the base of the sediments.

• Sedimentological modelling: of dynamicinterpretive type, it reproduces thesedimentation/erosion processes in the differentdeposition environments and thus allows us toestimate the distribution of the different facies,both organic and inorganic.

• Basin characteristics: given by the description of thephysical-chemical parameters (permeability, thermalconductivity, porosity, etc.) inside the differentfacies, it is necessary for oil system modelling.

• Temperature and pressure evolution modelling: itreconstructs the evolution in time of the pressureand temperature field in accordance with theexperimental well data.

• Hydrocarbon generation and expulsion modelling: itincludes the geochemical modelling of thegeneration phase of the different components of thehydrocarbons, which is strictly tied to the expulsion(primary migration) from the low permeabilitylayers (usually shale) of the source rock.

• Hydrocarbon migration and entrapment modelling:

it describes the movement of the hydrocarbons(secondary migration) expelled from the sourcerock, along routes of greater permeability(generally sands) to the traps, with a significantrole of the faults, which can act as barriers orpreferred paths according to their characteristics(see again Fig. 3). The different types of modelling quoted can be

performed in a strictly integrated manner or, as in thecase of the sedimentological model, can be achievedvia various methods and software with specificapplication ranges.

Both the complexity of geological modelling andthe need for the model to be shared among the differentmodellers (structural geologists, sedimentologists,geochemists, oil system modellers, etc.) appear obviousfrom this list. Today in many oil companies the work ofthe various experts within specialised sections isperformed simultaneously in a virtual reality roomspecially made and equipped for this purpose (Fig. 4).

Only recently have calculating power and graphicvisualisation instruments reached a level of adequatedevelopment with costs compatible with the spread ofthese new methodologies, opening up at the same timeto new potentials for development of modellingtechniques more advanced than nowadays ones, aswell as to the study of not yet clear aspects of thegeological evolution of the basin and the oil system.The great uncertainties of the parametres andprocesses involved can make the exploration risk seemarbitrarily large compared to the discovery of


EVALUATION AND DEVELOPMENT OF THE EXPLORATION

geostatisticalsimulations for maps: PSM

simulations

geologicalhypotheses for scenarios:

no fluid flow open to fluid flow

statistical distributionsfor parameters:

oil

gas

petroleum system modelling uncertainty evaluation

Fig. 3. Method used to assess ‘hydrocarbonrisk’: the various uncertainties of the source data translate into a statisticaldistribution of the possible volumes of oil and gas.

economically viable fields, but in reality the use of aprobabilistic approach shows that this is not the case.We have to distinguish between a radical uncertainty,linked to the interpretive choices of the modellers, andan uncertainty due to an incomplete knowledge of theparameters of the different types of modelling applied.If we introduce the concept of ‘solution space’, inwhich all the possible evolutionary histories of thebasin in question are included, we have the first typeof uncertainty producing several possible alternativescenarios, which correspond to dots in the solutionspace, and the second type of uncertaintycorresponding to clusters of dots/solutions aroundthose scenarios. This translates into a workingevaluation of the exploration risk in terms of volumeof hydrocarbons potentially trapped, expressed asprobabilistic distribution curves (see again Fig. 3).

The answer to the hydrocarbon explorationproblem is thus a probabilistic type evaluation, bothfor the geometric component of the potential field and for that relative to the trapped hydrocarbons,with the so-called deterministic solution being only an intermediate phase of the evaluation processfor exploration risk. Finally, the intrinsic non-linearity of modelled geological processesexcludes the possibility of determining a priori whatare the parameters and characteristics of extreme cases(pessimistic and optimistic) from those compatiblewith the available measurements, whilst it is on theother hand possible to obtain them a posteriori fromthe analysis of the different simulations carried out.

Modelling of different geological contexts Hydrocarbon reservoirs are located in sedimentary

basins whose formation (in terms of subsidence) iscontrolled first and foremost by tectonic processes.Tectonics also controls exhumation and uplift, whichlead to the formation of emerged areas and thus the

type and amount of sediments produced, which arethen deposited in the adjacent basin (Fig. 5). Climaticand palaeoceanographic factors are also fundamentalfor the type and distribution of sediments in the basin.These factors have a different role, with varyinginteractions, depending on the geological context.Quantitative geological modelling must therefore beable to relate and integrate various factors and provideaccurate predictions.

A number of geological modelling approaches areoutlined below. Given their scale and the processeshandled, some of these models are not usuallyconsidered as being closely related to the modellingwhich is of specific interest for hydrocarbonexploration and production. This choice is based onthe belief, held by a wide number of experts, thatgeological phenomena which are not immediatelyrelated to the reservoir also play an important part inits understanding. We could say that a lack ofunderstanding of these background signals is often thereason behind major failures. One significant exampleis the modelling of the thermal evolution of a basin.

Convergence contexts Two plates moving towards each other will result in

a geological regime of convergence (see Section



Fig. 4. Advanced Visualisation Center, Eni, San Donato Milanese.

IDROCARBURI

exhumation

relief

erosionsedimentation

basin

subsidence

Fig. 5. Diagram of the relationshipsbetween vertical movements and erosion and accumulation zones.

1.4.1). In a first stage, convergence is accommodated bythe subduction of the oceanic lithosphere. Subsequently,when subduction of the continental crust begins, boththe orogen, which normally has an associatedmorphological relief, and the adjacent sedimentarybasin, start to fully develop (Fig. 6). The orogen is boththe driving force behind basin subsidence and thesource of sediments which deposit there. The dynamicsof the subsidence of the basin, its environmentalcharacteristics during and after its sedimentation anddeformation are fundamental in determining thearchitecture of the basin, and thus, for example, thepresence of traps and fracturing. Between these twodomains – the orogen and the basin – is the fold-and-thrust belt, where sediments from the proximal part ofthe foredeep are first deformed, with considerableshortening, and then incorporated in the orogen.

Convergence contexts have played a particularlyimportant role in the history of hydrocarbonproduction in a number of countries, such as Italy,where most reservoirs are associated with foredeepbasins or with the outer parts of fold-and-thrust belts.

The continental collision zones and, as mentioned,the outer part of fold-and-thrust belts particularly areof great interest for exploration and will attractincreasing attention over the next few years. The newplays identified will generally be below the first thrustsheets, namely at levels located in areas that are avirgin territory for exploration. Yet these areas are alsoassociated with high operating risks, given the poorquality of seismic images produced by these complexgeological contexts. These are the very areas wheremodelling provides an important contribution tolowering risks.

Large scale: subduction processes and continentalcollision

The dynamics of subsidence and processes takingplace within areas affected by subduction andcontinental collision are one of the most interestingaspects of tectonic studies. Special focus is given bothon the processes that enable the exhumation of rocksdeformed at major depths (several tens of kilometres)and on the role of physical factors (including climaticaspects) affecting the dynamics of the system. For thispurpose, analogue and numerical modellingtechniques are employed.

Analogue techniques have been in use for severalyears now, but only recently has it been possible toinvestigate the complex dynamics of subduction zones,with the aid of new materials and an understanding ofthe rheology involved in these types of geologicalprocess. Analogue models have been particularlyeffective at describing the different types ofsubduction and deep evolution of the subducted plate.

Its geometry, its permanence above the discontinuitylocated at a depth of 670 km, and the episodic natureof mantle convection, have allowed predictions to bemade on the distribution of old plates in the deepmantle. These hypotheses have enabled a link to beestablished with tomographic studies (Faccenna et al.,2003).

Over the last few years, great progress has beenmade in the numerical modelling of subduction andcollision processes, with a significant focus on theexhumation of deep rocks. One of the most importantconclusions reached by these studies is that high-pressure-, low-temperature-metamorphosed rocks maymove upwards along the subduction plane. This ismade possible by a number of factors, such asrheological weakening and the extrusion of weak andductile rocks (Burov et al., 2001).

It is also significant to recognize howgeomorphological phenomena, such as erosion,sedimentation, are relevant in the development ofprocesses taking place in collision zones. Modelsfrom different American schools (Montgomery et al.,2001) show how the geometry of the orogen andkinematics of rocks inside it are greatly affected byprocesses taking place on the surface. This in turninfluences the production of sediments and thus thetype of deposits which may be present in foredeepbasins (see again Fig. 6).



foredeep foredeep

load

fold-and-thrust belt

subducting plate

Fig. 6. Diagram of tectonics incontinental collision contexts. Top, theinternal architecture of the sedimentarybasin, which is dependent on both largescale subduction processes and on the geometry and kinematics of overthrusts.

The inclusion of geomorphological processes innumerical models is far from simple; it involvescomplex processes, accompanied by numerousuncertainties, as there is little knowledgeof the parameters and equations governinggeomorphological processes (such as erosion), andparticularly on the time scale quantitativegeological models refer to, i.e. 105-107 years. Thisis a general and fundamental problem, as there is agrowing awareness of the importance of non-linearaspects of considered processes, where smallvariations in parameters may be seeminglyunimportant but can lead to major differences in thefinal results.

In addition, numerical models of convergencezones often have large margins of error, associatedwith the thermal component of the model. This isbecause major physical parameters, such as rockconductivity, are not fully known. In fact, laboratorymeasurements are taken on limited-size samples,which provide partial descriptions of complex systemsthat, as in the case of fracturing fields and movingfluids, may play a fundamental role.

Fold-and-thrust beltsAnalogue modelling has been of primary

importance in investigating geological domainscharacterized by fold-and-thrust belts, producing alarge number of studies with highly significantresults, particularly for what concerns the dynamicbehaviour of the geological context. Mostexperiments are based around the theoreticalframework of the critical taper theory (Dahlen et al.,1984), which defines the relationships between theform and dimensions of the orogenic wedge on theone hand and the dynamic parameters inside and atthe base of this wedge on the other. A number ofstudies have led to an increasingly sophisticateddefinition of the role of different types of rheologicalbehaviour (Smit et al., 2003), which have animportant controlling effect on both the form of thewedge and its internal architecture, i.e. on parameterssuch as vergence, size and entity of overthrusts.

Other considerable developments have involvedexperiments where the stresses occurring duringdeformation are measured (Nieuwland et al., 2000);these studies will also improve the correlation betweenanalogue and numerical experiments.

As concerns the numerical modelling of belts, thefirst important steps forward involved implementingnumerical modelling routines to construct balancedgeological sections in which the conservation ofmasses is respected. So-called kinematic programmesare used, with a very limited or entirely absentdynamic component. This implies substantial input by

the operator, who must enter the faults, determine theirgeometries, etc. The result is then compared with theactual situation to verify the accuracy of thedeductions made.

Some of these models have been further developedto predict geometries and to a lesser extent, the type ofsediments which deposit during and after shortening.It is clear that the geometries of fold-and-thrust beltsas well as the type of sediments are directly affectedby the geometric features of faults and by thekinematics of their activation (den Bezemer et al.,1999; Salvini and Storti, 2002).

The great progress being made, which shoulddevelop further in the future, concerns an increasinglymechanical approach and greater integration with thedescription of thermal events and movement of fluids.The integration of a thermal component impliessolving significant numerical problems, as thehorizontal movements related to overthrusts play aconsiderable role. This type of modelling can verify, inquantitative terms, different scenarios such ashydrocarbon generation and migration and fluidcirculation fields.

Foredeep basins and relationships betweenthe orogen and the basin

Foredeep basins are subsiding areas that form closeto fold-and-thrust belts, because of the lithosphericload applied by the orogen (see again Fig. 6). In theseareas, modelling, and above all numerical modelling,has played a vital role and will certainly developconsiderably.

The first models focused on the form anddimensions of foredeep basins and concerned staticmodelling, which did not address the movement oforogenic masses. These models targeted depositionbasins where sediments simply filled up the zonelocated between the base of the water column and thetop of the basement, without considering the geneticlink with sediment production areas.

Subsequent developments led to the inclusion inthe models of the time factor and the processesgenerating, transporting and depositing the sediments.These models can also consider the relative movementof the orogen inside the basin. Through importantassumptions made on climatic and geomorphologicalprocesses, the models can be used to predict thequantity and type of sediments in the basin, which isof fundamental importance for the oil industry.However, these models are also limited, as they arebidimensional and do not take into account sedimenttransport along the basin axis. Indeed many systemsexist, such as the Apennine foredeep basin, wheresediments are transported parallel to the belt even forup to hundreds of kilometres.



The approach used in the only models which candescribe three-dimensional situations (García-Castellanos et al., 2002) foregoes the accuracy of thephenomena described to the advantage of three-dimensional processing, which can also consider thetectonic component.

Extensional basinsA considerable number of oil fields is located in

sedimentary basins which, in terms of bothdepositional geometries and thermal evolution,develop in geological contexts where the lithosphere issubject to extension (see Section 1.4.1). These regionsare extremely significant for hydrocarbons andinclude, for example, the oil provinces of the NorthSea and the West African margin.

During extension, vertical movements and thedestruction/creation of the accommodation space aregenerated by two processes: the movements of crustalblocks along the faults and changes in the weight ofthe lithospheric column (Fig. 7). The detailed history of subsidence evolution, on bothfault block and basin scale, is essential forreconstructing a complete picture of sedimentary basingeometries.

After a first, somewhat general modellingstage, which began in the 1990s, a widespreadbelief took hold that segments of the lithospherewith different original characteristics can react indifferent ways to extension. As proof of this,different parts of the world have extensionalstructures with major variations in terms of theduration of extension, the width of the areainvolved, the extent and the direction of verticalmovements, and the presence of magmatism, etc.These differences have a direct impact on thevarious factors that are significant for hydrocarbonexploration and production. This is particularly trueof one of the frontier areas of hydrocarbonexploration: deep and ultradeep waters (�1,500 m),including the distal regions of the Gulf of Mexicoand of the western margin of the African continent,which are high-potential areas and are the target ofmajor technological and financial investments.These situations occur in passive continentalmargins characterized by a thick sequence of post-rift sediments. Thick layers of evaporites are oftenpresent at the base of these sequences, so thequality of seismic images is often insufficient tocorrectly reconstruct the geometry and thesedimentological characteristics of the sin-riftsequences, which are of fundamental importance.In these cases, modelling acquires a fundamentalrole in reducing the risks associated with this typeof exploration.

Evolution on a lithospheric scaleWith the major advances made in computer

power, many numerical studies have been carried outon the physical and geological conditions thatcontrol the different behaviour of various types oflithosphere subject to extension. The distinctionbetween wide rifts, narrow rifts and core complexeswas systematically made for the first time in the1990s (Buck, 1991). The mechanical-thermalconfiguration of the lithosphere at the beginning ofextension, and the thermal conditions during riftinghave proved to be very important factors (Bassi etal., 1993; Govers and Wortel, 1995; Huismans andBeaumont, 2002).

Numerical modelling studies have also provided anew and more sophisticated understanding of thedynamic and tectonic changes, which take place insidethe lithospheric plate subject to extension. One of themost evident phenomena that can be observed in mostpassive margins, is the presence of an extensionalbasin abandoned before the appearance of ocean crust.This involves the lateral migration of the site ofextension, and is due, for example, to the hardening ofa lithosphere segment subject to slow extension (vanWijk and Cloetingh, 2002).

The possibility of considering the role ofmagmatism before and after extension has beenparticularly important, above all in hydrocarbonexploration and production. The traditionaldistinction between active and passive rifts has beendiscussed by Husimans et al. (2001). Whenlithospheric thinning rates are extremely high, theasthenosphere, behaving as if it were a diapir, movesupwards because of the lower density of thesurrounding rocks and impacts the entire tectonicsystem, both in thermal and mechanical terms. Onlysophisticated, quantitative studies can predict the



extensional basin

asthenosphere

mantle

crust

rift shoulder

Fig. 7. Diagram of processes taking place in continental extensional zones. The accommodation space is the result of two processes: the crustal-lithospheric thinning and the movement of fault blocks.

thinning rates required to trigger off thesemechanisms. Understanding the relationshipsbetween continental extension and magmageneration is also fundamental. In nature, there is astriking contrast between margins with abundantmagmatic rocks (volcanic margins, such as theNorwegian margins) and margins without theseformations (the Iberian margin). The fact that thesephenomena have not yet been understood inquantitative terms, proves once again that knowledgeof thermal parameters is insufficient.

As in the case of continental collision processes,geomorphological processes are also extremelyimportant in studying extensional systems. In certainconditions, particular system sectors, such as ‘riftshoulders’, can be uplifted and consequentlyexposed to erosion by atmospheric agents (see againFig. 7). The removal of material and the resultingchange in isostatic conditions has an importantimpact on the actual evolution of the system (Burovand Cloetingh, 1997).

Analogue modelling techniques are often used tounderstand and predict lithospheric extensionphenomena. Without a doubt, the most topical issuesare linked to the definition of the conditions requiredfor different types of extension to develop (Whitmarshet al., 2001). There is still major debate as to theapplicability of these models, which do not include athermal component and cannot apply tensional stressto the system.

Evolution on a basin scaleThe origin of numerical modelling for extensional

basins can clearly be traced back to McKenzie (1978)who was the first to establish quantitative relationshipsbetween lithospheric thinning and the geometry ofextensional basins. McKenzie’s model was thendeveloped considerably, with the inclusion of lateralheat transmission, lithospheric rigidity, finite and non-instantaneous rifting duration, differential crust andlithospheric mantle thinning, etc. However the mostconsiderable improvement was made with theinclusion of faults (Kusznir and Ziegler, 1992; TerVoorde and Cloetingh, 1996). With the addition of thegeometries and kinematics of faults, detailedpredictions on the internal filling structure of thesedimentary basin could be made. These models arestill based on kinematics, where the operatorconfigures the geometric characteristics andkinematics of faults, rather than the model generatingthem. Investigating the actual development ofextension, with spatial and temporal variations, is ofparamount importance in providing a detailedreconstruction of the thermal evolution of modelledsedimentary basins.

Crustal-lithospheric folding contexts The sedimentary basins described so far are

generally characterized by prominent faults andstrong horizontal deformations (shortenings orextensions). However, scenarios where sedimentarybasin development is associated more with folding ona crustal-lithospheric scale, rather than with faults, arefrequent (Cloetingh et al., 1999). According to thesemodels, sedimentary basins develop in syncline zonesand are laterally bounded by anticlines (Fig. 8). Thesebasins have only been recognized fairly recently andthe most important studies, as concerns modelling,have been conducted with a numerical approach. As aresult, quantitative relationships between thethermodynamic structure of the lithosphere and wavelengths and amplitudes of lithospheric folding can beestablished. As mentioned previously, even in the caseof lithospheric folding, erosion in emerged areas has aconsiderable impact on basin evolution and on theinternal architecture of sedimentary filling.

Dynamic models (with finite elements numericalcodes) have also made it possible to describe the stressand deformation fields of systems subject tolithospheric folding. The syncline zones, in particular,are characterized by strong compression which mayeasily give rise to widespread fracturing, which is afundamentally important phenomenon for accuratelypredicting and managing oil fields.

Sedimentological modellingThe primary aim of this type of modelling is to

predict the distribution of different types of sedimentsinside a sedimentary basin. In the field ofhydrocarbons, it is clearly of fundamental importanceto be able to predict the position and volume of sandbodies.

As mentioned, oil exploration in recent years hasshifted its focus to deep and ultradeep waters in



erosionin anticlines

sedimentary basinsin synclines

Fig. 8. Diagram of the phenomena which occur when the lithosphereis subject to horizontal compressionalstress and folding. Subsidence takes place in the synclines, and sediments may deposit.The anticlines form the margin of basins;when they emerge above sea level, erosion may occur.

Western Africa, Brazil, the Gulf of Mexico, etc. Theseareas are characterized by major sequences of turbiditedeposits, where the porous levels constitute thereservoir. In deep waters, exploration studies can makeuse of indirect data (seismic sections, gravimetric andmagnetometric modelling), while direct data is notavailable, or very limited (in fact very few wells havebeen drilled in frontier areas).

To reconstruct the geometries of these deposits anddistribution of different facies, geological andsedimentological models must be developed, whichincorporate information from areas where these typesof sediments are exposed to a fair extent, as in theApennines and Pyrenees (Mutti and Ricci Lucchi,1972; Mutti and Normark, 1987, 1991; Mutti et al.,1988). Advanced methodologies and computerprogrammes can integrate geophysical data, acquiredin the basin where exploration is carried out, with landdata for the mathematical development ofsedimentological models.

Analogue modelling is normally carried out onlarge systems, which can take account of thesedimentary basin, sea level variations and impact oftectonics, in a fairly schematic way (Paola, 2000).

As recognition has gradually been given to theimportance of processes taking place in thedepositional area, in order to determine the type andamount of sediments which may be deposited in abasin, studies have been conducted to quantify therelationships between the morphology of an area andits climate. These studies are complex as they arebased on poorly known parameters and equations(even in quantitative terms). The progress made in thelast few years has demonstrated the importance ofthese approaches. Analogue modelling is particularlycomplex for sedimentary basins, due to the difficultiesin correctly translating the laboratory scale to theactual scale.

Conclusions

In the field of numerical modelling, the progressmade by computer techniques and computing powerhas led, as already stressed, to the use of increasinglysophisticated and complex models and this extremedevelopment is causing a sort of ‘growth crisis’. Infact the increment in the complexity of the system, andthus in the ability to consider different phenomena, hasled to increasingly fewer restrictions and hence adecreased prediction capacity. Often the results ofthese models cannot be reproduced and arecharacterized by major convergences and divergences.The term convergence is used to define situationswhere the same result is obtained starting from verydifferent configurations. The term divergence is used

to define numerical experiments where small initialdifferences (well below the margin of error) lead tocompletely different results. Highly sophisticatedmodels can reproduce any type of actual context andthus risk to become ineffective. It is clear that this ismainly related to the non-linear nature of the naturalphenomena considered.

Another fundamental problem concerns the valuesused for numerical parameters. Obviously, the greaterthe resolution of developed models, the greater thedependence on the parameters used. In practice, theseparameters are often not known or known only to asmall extent. The underlying problems concern thespatial and temporal scale. Laboratory measurementscan without doubt accurately determine the physicalcharacteristics of rock samples, such as thermalconductivity. However these values reveal little aboutthe behaviour of domains on a scale of tens, hundredsor thousands of metres. The values of physicalparameters characterizing these units are the overallresult of a number of phenomena. The same applies tothe time scale: the greater our ability to directlymeasure geological phenomena, such as movementsalong faults or the transport of material along a slope,the greater our understanding that the rates of thesemovements are not constant but depend on the timescale.

Debate as to how we can effectively improve, inthe future, the prediction capacities of quantitativemodels is ongoing and it is not easy at present toidentify certain trends. On the one hand, there is agreat deal of pressure to increase the complexity ofnumerical models used. On the other hand, there is agrowing need to develop simple models, which allowfor a true understanding of the physical characteristicsof the system, rather than its simple statisticaldescription. This calls for the problem to besubstantially simplified, in order to identifyfundamental control factors. To this end, it isimportant to merge different types of data anddisciplines, in order to offset diverse approaches, aswell as different types of modelling, for exampleanalogue and numerical modelling (Persson et al.,2004).

With an entirely different focus, some studies aremoving away from the prevailing deterministicapproach, to adopt a philosophy of self-organized-criticality upon which natural systems are apparentlybased (Bak, 1997).

If the above is true, and namely if there is a strongtendency to adopt simpler models, the geologicalcomponent of modelling will become increasinglyimportant. Only with an accurate understanding of thegeological context where hydrocarbon explorationtakes place can the simplifications mentioned



previously (for example the modelling of turbiditesystems, which are based on the study of outcroppingsequences in the Pyrenees) be made correctly, whereassimplifications that do not concern the specificregional context have a strong probability of producingerroneous results. This implies a renewed commitmentto understanding regional geology, as well as thephenomena which traditionally are not considered inrelation to hydrocarbon exploration, such as data onthe lithosphere structure.

References

Bak P. (1997) How nature works. The science of self-organizedcriticality, Oxford, Oxford University Press.

Bassi G. et al. (1993) Contrasting styles of rifting. Models andexamples from the eastern Canadian margin, «Tectonics»,12, 639-655.

Bezemer T. den et al. (1999) Numerical modelling of fault-related sedimentation, in: Harbaugh J.W. et al. (edited by)Numerical experiments in stratigraphy. Recent advancesin stratigraphic and sedimentologic computer simulations,Tulsa (OK), Society for Sedimentary Geology, 62, 177-196.

Buck R.W. (1991) Models of continental lithospheric extension,«Journal of Geophysical Research», 96, 20161-20178.

Burov E., Cloetingh S. (1997) Erosion and rift dynamics.New thermomechanical aspects of post-rift evolution ofextensional basins, «Earth and Planetary Science Letters»,150, 7-26.

Burov E. et al. (2001) A thermomechanical model ofexhumation of high pressure (HP) and ultra-high pressure(UHP) metamorphic rocks in alpine-type collision belt,«Tectonophysics», 342, 113-136.

Cloetingh S. et al. (1999) Lithospheric folding. Primaryresponse to compression? From Central Asia to Paris basin,«Tectonics», 18, 1064-1083.

Dahlen F.A. et al. (1984) Mechanics of fold-and-thrust beltsand accretionary wedges. Cohesive Coulomb theory,«Journal of Geophysical Research», 89, 10087-10101.

Faccenna C. et al. (2003) Subduction and the depth ofconvection in the Mediterranean mantle, «Journal ofGeophysical Research», 108.

García-Castellanos D. et al. (2002) Modelling the evolutionof the Guadalquivir foreland basin (South Spain),«Tectonics», 21.

Govers R., Wortel M.J.R. (1995) Extension of stablecontinental lithosphere and the initiation of lithosphericscale faults, «Tectonics», 14, 1041-1055.

Huismans R.S., Beaumont C. (2002) Asymmetric lithosphericextension. The role of frictional plastic strain softeninginferred from numerical experiments, «Geology», 30,211-214.

Huismans R.S. et al. (2001) Dynamic modeling of the transitionfrom passive to active rifting. Application to the Pannonianbasin, «Tectonics», 20, 1021-1039.

Kusznir N.J., Ziegler P.A. (1992) The mechanics ofcontinental extension and sedimentary basin formation.

A simple-shear/pure-shear flexural cantilever model,«Tectonophysics», 215, 117-131.

McKenzie D. (1978) Some remarks on the development ofsedimentary basins, «Earth Planetary Science Letters», 40,25-32.

Montgomery D.R. et al. (2001) Climate, tectonics, and themorphology of the Andes, «Geology», 29, 579-582.

Mutti E., Normark W.R. (1987) Comparing examples ofmodern and ancient turbidite systems. Problems andconcepts, in: Leggett J.K., Zuffa G.G., Deep water clasticdeposits. Models and case histories, London, Graham &Trotman, 1-38.

Mutti E., Normark W.R. (1991) An integrated approach tothe study of turbidite systems, in: Weimar P., Link M.H.(edited by) Seismic facies and sedimentary processes ofsubmarine fans and turbidite systems, New York, Springer,75-104.

Mutti E., Ricci Lucchi F. (1972) Le torbiditi dell’AppenninoSettentrionale. Introduzione all’analisi di facies, «Memoriedella Società Geologica Italiana», 11, 164-199.

Mutti E. et al. (1988) Sedimentation and deformation in theTertiary sequences of the Southern Pyrenees, Università diParma, Istituto di Geologia.

Nieuwland D.A. et al. (2000) In-situ stress measurements inmodel experiments of tectonic faulting, in: Lehner F.K.,Urai J.L. (editors) Aspects of tectonic faulting. In honourof George Mandl, Berlin, Springer, 155-166.

Paola C. (2000) Quantitative models of sedimentary basinfilling, «Sedimentology», 47, 121-178.

Persson K. et al. (2004) River transport effects on compressionalbelts. First results from an integrated analogue-numericalmodel, «Journal of Geophysical Research», 109.

Salvini F., Storti F. (2002) Three-dimensional architectureof growthstrata associated to fault-bend, fault-propagation,and décollement anticlines in non-erosional environments,«Sedimentary Geology», 146, 57-73.

Smit J.H.W. et al. (2003) Deformation of brittle-ductile thrustwedges in experiments and nature, «Journal of GeophysicalResearch», 108.

Ter Voorde M., Cloetingh S. (1996) Numerical modellingof extension in faulted crust. Effects of localized and regionaldeformation on basin stratigraphy, in: Buchanan P.G.,Nieuwland D.A. (edited by) Modern developments instructural interpretation, validation and modelling, London,Geological Society, 283-296.

Whitmarsh R.B. et al. (2001) Evolution of magma-poorcontinental margins from rifting to seafloor spreading,«Nature», 413, 150-153.

Wijk J. van, Cloetingh S. (2002) Basin migration causedby slow lithospheric extension, «Earth Planetary ScienceLetters», 198, 275-288.

Giovanni BertottiDepartment of Tectonics and Structural Geology

Vrije UniversiteitAmsterdam, Netherlands

Paolo RuffoEni - Divisione E&P

San Donato Milanese, Milano, Italy



2.4.2 Basin modelling for petroleum exploration

IntroductionThe word ‘modelling’ can be used for numerous

objects such as simple theoretical concepts,analogical modelling, or numerical modelling(Schneider, 1989). Only numerical models able tohandle the generation, migration and accumulation ofhydrocarbons will be considered here. Basinmodelling was born during the 1980s (see Doligez etal., 1986) following Tissot’s pioneer works ongenerating hydrocarbons from the transformation oforganic matter under the conjugate effects oftemperature and time (Tissot, 1969).

Basin modelling tools have been used within oilcompanies for exploration during the last fifteenyears (Doligez et al., 1986; Lerche, 1990; Ungerer etal., 1990). They provide a strategy for optimizingexploration in frontier areas and evaluating new playswithin well-explored basins. Recently, a newgeneration of basin models capable of simulating in3D the entire petroleum system, has been used forexploration purposes in oil companies (Coelho et al.,1996; Düppenbecker et al., 1998; Gerritsen et al.,1996; Grigo et al., 1993; Hantschel and Synofzik,1997; Mello et al., 1998; Moeckel et al., 1997a,1997b; Schneider and Faille, 1997; Smith et al.,1998; Szalay et al., 1992; Unander et al., 1997;Wygrala et al., 1997).

Unidimensional (1D) basin models are useful forthe reconstruction of the thermal history of the basinand the evaluation of the maturation of the organicmatter. In a sedimentary basin context, the 1Dapproach is satisfactory for these purposes becausethe thermal transfers are mostly vertical. Indeed,thermal convective transfers are most frequentlynegligible. Furthermore, two-dimensional (2D) basinmodels provide the possibilities of performing anevaluation of the pressure history and an appreciationof the hydrocarbon migration and reservoir filling.However, these evaluations can only be qualitativebecause fluid flow (water, oil, and gas) is mainlyconvective and therefore sensitive to three-dimensional (3D) geometry and anisotropy. This iswhy 3D basin modelling tools have been developed(Schneider et al., 2000). These tools allow us to

simulate thermal history, pressure evolution,hydrocarbon generation, and multiphase fluid flowmigration in the three dimensions of space.

In the first part of this paper, the main goals ofbasin modelling are exposed. Then the general contentof a basin model is explained. Lastly, the workflowused for basin modelling is illustrated through anexample.

Main goals of basin modellingPetroleum accumulations are the result of several

physical processes, which interact at geological timescale (Fig. 1). The basin geometry is controlled bysedimentation, erosion, tectonic displacements, andsediment deformation generally called compaction.

The temperature in each part of the basin is theresult of the thermal transfers from the deeper part ofthe crust toward the surface. The conjugate effects oftime and temperature transform the organic matter,which has been deposited during sedimentation, intohydrocarbons during the maturation process. Thegenerated hydrocarbons are then expelled from thesource rocks. Once expelled from the source rocks, thehydrocarbons can migrate. The migration process iscontrolled by the permeability distribution. The maindriving forces of hydrocarbon migration are gravity,viscous forces, and capillary forces. When thepermeability contrast is large enough to slow the flow,the hydrocarbons are trapped (at the geological scale)and a reservoir is born (Tissot and Welte, 1984; Hunt,1995).

Generally after the discovery of a potential trap,the explorationist has to answer the three followingquestions:

287VOLUME I / EXPLORATION,PRODUCTION AND TRANSPORT


sedimentation erosion

migration

maturation

expulsion

source rock compaction/diagenesis

displacement

accumulationgas

Fig. 1. Vertical section of a petroleum system.

• Does the trap contain hydrocarbons? • Is the trapped volume of hydrocarbon of

economical interest? • Is the quality (e.g. composition) of these

hydrocarbons interesting from an economical pointof view? Now, we come to the subsidiary question: what are

the risks of finding excess pore pressure duringdrilling?

The objective of basin modelling is mainly to helpanswer the four questions above. More specifically,the aim of a basin model is to numerically simulatethe hydrocarbon accumulations at basin scale and atgeological time scale. These numerical modelsaccount for kinematics, sedimentation, erosion,compaction, heat transfer, diagenesis and fluidtransfers.

Description: physical concepts and equationsThe first step during the building of a numerical

model is the recognition of the physical processesthat should be accounted for and the relatedmathematical equations that quantify them. Generallythe equations contain parameters that must becalibrated. Lastly, numerical methods should beimplemented in order to solve the problem, which isgenerally formed as a non-linear system of partialdifferential equations.

For the sake of clarity, the physical concepts andthe equations will be written, in the following, for asimplified compositional two-phase flow. In thismodel only two mobile phases (water andhydrocarbon) are considered, and four components(water, oil, gas, and coke) are accounted for. The porous medium (or the lithology) is composed of immobile (or solid) components(minerals, kerogen, and coke) and mobile components(oil, gas, and water). The water component is presentonly in the water phase. Minerals, kerogen and coke are present in the solid phase, oil and gas in the hydrocarbon phase. The porous medium is characterized by its initialcomposition which includes the initial mass ofkerogen.

Mass balance. The first principle that is accountedfor is mass balance, which concerns the solids and thefluids (Schneider et al.,1990).

For each phase a�{s, w, h} (s�solid, w�water,h�hydrocarbon), the mass balance equation is:

∂[1] div (/a raVa)�1 (/a ra)�ra qa∂ t

where /a is the volumetric fraction, ra is the density,qa is the volumetric source term and Va is the meanvelocity. We have the following relationships:

/s�/w�/h�1 and /�/w�/h, where / is the porosityof the porous medium.

Momentum equation. The momentum equation issimplified as follows:

∂ Pb[2] 12�rb g∂ z

where Pb is the lithostatic pressure (weight of thesedimentary column), g is the gravity and rb isthe bulk density of the porous medium saturatedby the fluids. This bulk density is given by:rb�/srs�/ rf , where rf is the mean density ofthe fluid defined by: rf�Sw rw�Sh rh. Sa is thesaturation (volumetric fraction) of the phase a inthe fluid (Sa�/a //).

Heat equation. The heat transfers are computedusing the energy mass balance coupled with theclassical Fourier equations, which describe conduction and convection. When the brittle crust is considered, or in the particular case ofradioactive sediments (e.g. hot shales), the radioactivesource terms should be considered in the energybalance.

The energy equation (or heat equation) is thenwritten as follows:

∂[3] 12�

a�ra/aCaT��∂ t

div ��lb grad(T)�a�ra/aCaTVa��qr

where Ca is the heat capacity of the phase a, T is thetemperature in Kelvin, lb is the bulk thermalconductivity of the porous medium saturated by thefluids a. It should be noticed that the mechanicalenergy dissipation is neglected. qr represents theradiogenic source term and the heat source termrelated to thickness modification.

Rheology. Generally, only internal deformationsare described through a rheology; displacements areimposed by the kinematics. The rheology can be assimple as a relationship between the porosity and theeffective stress (Smith, 1971; Schneider et al., 1996),or can be a tensorial relationship (Schneider andFaille, 1997). This rheology may be completed with amechanism, which describes the hydraulic fracturingand the related permeability evolution (Schneider etal., 1999).

Compaction at basin scale and at geological timescale is supposed to be vertical. This choice is theresult of a compromise between accuracy and costs interms of CPU time (Lamoureux-Var et al., 1998).The behaviour law is then given by a volumetricrheology (Schneider, 1993; Schneider et al., 1994,1996):



d/ ds[4] 12��b(s)12�a(/,T)s

dt dt

In the previous equation s is the mean effectivestress defined as: s�[(1�2Ko)/3](Pb�bPf ), where Kois the ratio between the horizontal stress and thevertical stress, b is the effective stress coefficient(Schneider et al., 1993) and Pf is the mean porepressure, which is defined by: Pf�SwPw�ShPh.

Cracking. The transformation of the organicmatter into hydrocarbons by the conjugate effect oftime and temperature is described through first orderkinetics chemical reactions similar to the onesdeveloped by Tissot (1969), and Tissot and Espitalié(1975). The secondary cracking is also described byfirst order chemical reactions (Béhar et al., 1992,1997).

The hydrocarbon generation is performed with aconservative physical model which considers threecomponents (oil, gas, and coke). In this model, the oiland gas components are entirely in the hydrocarbonphase, and the water component is present entirely inthe water phase.

During the primary cracking, the kerogen istransformed with n parallel reactions, into oil, gas andcoke.

x1 → ao1 Oil � ag

1 Gas �a1c Coke

� → � � � � �

[5] Kerogen � xi → aoi Oil � ag

i Gas �aci Coke

� → � � � � �

xn → aonOil � ag

nGas �anc Coke

xi is the normalised partial potential of reaction i. It isa property of the kerogen which obeys the followingrelation:

i�1

n

�xi0�1

aoi (respectively a g

i and aci ) is the oil (respectively the

gas and coke) stoichiometric coefficient of reaction i.We have: ao

i �a gi �ac

i �1.Each of these elementary reactions is supposed to

be controlled by a first order kinetic given by thefollowing equation:

dxi[6] 12��ki xi with ki�Ai e�

Ei1

RT

dt

A is the frequency factor, E is the activation energy,R is the perfect gas constant, T is the temperature inKelvin.

The oil produced by the primary cracking is thentransformed, during the secondary cracking, into gasand coke. This reaction is supposed to also becontrolled by a first order kinetic given by thefollowing equation:

[7] Oil→ bg0Gas�bc

0Coke k0�A0e�

Eo1

RT

bg0 and bc

0 are the stoichiometric coefficients of thereaction which respect the following condition: bg

0�bc0�1.

In this particular model, we are only consideringnon-compositional transport of the hydrocarbons; thusthe secondary cracking can only be implemented inthe source rock where the composition in terms of oiland gas is still known. The result of the crackingmodule is the definition of part of the source terms(qa) used in the mass balance equations [1].

The transformation ratio (TR) of the organic materis then given by:

TR�1�i�1

n

�xi

Equations of state. The state of the fluids isdescribed by one or more state equations that are oftensimplified to a straightforward relationship, whichrelates density to pressure and temperature(Rudkiewicz et al., 1997).

Fluid flow. It is generally accepted thathydrocarbons migrate in separate phases from water,even if part of the light hydrocarbons may dissolve anddiffuse in water. The main driving forces forhydrocarbon migration are buoyancy, capillary forcesand pressure gradients.

Fluid flow in porous mediums is simulated withDarcy’s equations that have been generalised toaccount for multiphase compositional flows (Marle,1972). In some cases, solubilization of specificspecies in water (e.g. methane) and their transport bydiffusion should be accounted for (Lamoureux-Var etal., 1998).

The fluid is supposed to satisfy the generalisedDarcy laws. This is its mathematical formulation foreach of the phase a�{w, h}:

[8] Ua�/a(Va�Vs )��k�

ha(grad(Pa)�ra g)

Ua is the Darcy velocity of the phase a in theporous medium, k

�is the intrinsic permeability tensor,

ha is the mobility of the phase a in the porousmedium, and Pa is the pore pressure of the phase a.The pore pressure of the two liquid phases are relatedby the capillary pressure Pc: Ph�Pw�Pc. The capillarypressure is a function of the porosity of the porousmedium and a function of the hydrocarbon (or water)saturation.

One of the most common simplifications is toneglect the excess pressure and the capillary pressure(Hubbert, 1953). In this case, the Darcy velocity isgiven by:

kra �Ua��11 K�grad (rwg(z�h))�rag�ma



where z is the depth below sea level and h theelevation of the water table. In offshore conditions(h�0) and assuming that the fluids are notcompressible, we can derive the following equation:

kra �Ua��11 (rw�ra)gK�grad(z)�ma

This is the equation used in models where migration iscontrolled by the structural topography of the top ofthe carrier bed (Sylta, 1993).

The other simplification consists in neglecting onlythe excess of pressure. In this case the Darcy velocityis given by:

kra �Ua��11 K�grad(rwg (z�h)�Pca)�ra g�ma

Still assuming offshore conditions and noncompressible fluids, we can derive the followingequation:

kra �Ua��11 K�g(rw�ra)grad(z)�grad(Pca)�ma

Now, if one assumes that migration isinstantaneous regarding geological time, the migrationcondition used in the model is:

g(ra�rw)grad (z)�grad(Pca)

This is the equation used in models wheremigration is controlled by percolation (Carruthers andde Lind van Wijngaarden, 2000).

Closure of the problem. The problem consists inthe resolution of a system mainly composed of 10equations with the 10 unknowns /a,Va ,Pa, T (3�3�3�1�10). Once the initial and boundaryconditions are given, the system is well posed.

Boundary conditions. At the upper boundary, the pressures are imposed by the atmospheric pressureand by the bathymetry. The temperatures are imposedas a function of the altitude or the water depth.

At the lower boundary, there is no fluid flux andthe displacements are imposed, as well as the heatfluxes or the temperatures. At the lateral boundaries,there is no heat flux and the displacements are onlyvertical. The fluid flux or the pressure may be imposedas a function of space and time.

Parameter evaluationOnce the physical laws are determined, their

parameters should be defined. The majority of themcould be measured directly on representative samplesof the sediments that are considered. This is the casefor the heat properties, for the parameters of theelasto-plastic part of the rheology, and for theparameters of the generalised Darcy’s equations.

Thermal parameters. As mentioned above, the heatproperties (capacity and conductivity) could bemeasured directly on representative samples of theconsidered sediments.

Rheological parameters. As already stated, the elasto-plastic parameters could be measured directlyon representative samples of the considered sediments.Thus, from field data and/or laboratory measurementsthe following function could be calibrated:

/a s /b ss�sm b(s)�1 exp��1 �1 exp��1 Ea Ea Eb Eb

1s�sm b(s)�1Ee

One of the major difficulties in basin modelling isthat a part of the processes acts at geological timescale. This is the case of the pressure-solutionmechanism that could be simulated with visco-plasticity (Schneider et al., 1996).

(1�/)s�0 and /�/min a(s)�555� mb(T)

s�0 or /�/min a(s)�0

The volumetric viscosity can reach values of 50GpaMa or 1,5 1022 Pa·s at 15°C (Schneider and Hay,2001). These values cannot be measured in thelaboratory, and only indirect methods based on fieldmeasurements, theoretical considerations, andnumerical modelling can be used.

Kinetics parameters. Hydrocarbons generated inbasins are either issued from kerogen cracking throughprimary cracking (Tissot et al., 1987) or throughsecondary cracking of other hydrocarbons (Béhar etal., 1992). It was soon recognised that kineticsequations would correctly model hydrocarbongeneration and that kinetics parameters could bederived from laboratory experiments (Ungerer andPelet, 1987). The kinetic formulation replaced the firstapproach based on TTI, which was a simple empiricalparameter (Waples, 1980). However, the diversity ofexperimental devices that have been used and thedifferent experimental conditions led to a wide rangeof kinetics parameters (Ungerer, 1990). Hence,extrapolated from geological conditions, they resultedin large differences in the oil and gas windows(Waples et al., 1992a, 1992b).

Recent works have been performed on moleculartracers (Tang and Béhar, 1995) and mass balancecomparisons between open and closed systems (Béharet al., 1997). They have shown that compositionalbalances and kinetics parameters are reasonablysimilar for selected kerogens of Type I, II and II-S,independently of the experimental device.



Fluid flow parameters. One other difficulty lies inthe space scale. Indeed, the average cell sizes used inthe numerical models are very often some hundred ofmeters in each direction. Under these conditions theprobability that a plug measurement of permeability berepresentative of the permeability of the whole cell isvery weak. The plug measures only a few centimetersand the cell may contain fractures, heterogeneities,precipitation zones, etc. For what concerns thepermeability field, it is first evaluated with theknowledge of the lithology distribution, which could bethe result of a sedimentation model (Granjeon andJoseph, 1999). Then, the permeabilities are calibratedin order to mimic the observed pressure field.

The intrinsic permeability tensor is written as theproduct of an anisotropy tensor by the intrinsicpermeability: k

��a

�k(/). The intrinsic permeability is

computed with the modified Koseny-Carman formula(Schneider et al., 1996):

0,2 /m

k(/)� 11 111S2 (1�/)2

where S is the specific surface area of the porousmedium, and m is an exponent, which generally equals 3.

The previous model does not account for thepetrophysical changes, which occur during thetransformation of minerals. For example the smectiteinto illite transformation, which occurs above 60°C, and the kaolinite into illite transformation,which occurs above 110°C, may modify drasticallythe shale permeability. Recent models (Schneider etal., 2003) consider the second reaction, which isassumed to be active in the example of the Mesozoicmudstones of the Egersund Basin (NorwegianContinental Shelf).

The mobility of the phase a is the ratio of therelative permeability with the fluid viscosity:ha�kra (Sa )/ma(T ). The fluid viscosities (water andhydrocarbons) are generally a function of thetemperature and may be given by the Andradeformula. The relative permeabilities are generally afunction of the fluid saturations.

Solving the equationsAfter having tested the existing numerical

methods (i.e. finite differences, finite volumes, finiteelements), the finite volume has been chosen (Faille,1992). This method consists in integrating the set ofpartial differential equations in each cell; and thendiscretizing the resulting equations using finitedifference methods. This method has been selectedbecause it is locally conservative, which is acompulsory property for solving the transportequations. Finite elements methods do not respect

this condition (Bouvier, 1989; Faille et al., 1994,1996).

Once the differential system is discretized, theresulting non-linear system is solved by iterativemethods (Newton). The improvement of the predictionof these numerical models has led to a need for accuracy. This is generally correlated with anincrease in the number of cells that is directly related to the number of unknowns. Thus the increasein size of the linear systems that have to be solved leads to the development of efficient solvers for scalar or parallel computers (Scheichl et al.2003).

Furthermore, in order to solve the three-phase flowin a basin cut by faults along which blockdisplacements can occur, Domain DecompositionMethods (DDM) are now used (Schneider et al.,2002). In these methods, the faults are considered assubdomains with their own geological properties.

Work flowThe methodology used in sedimentary basin

modelling is now well established. It is more or lessthe same for 3D models with simple geometry(Schneider et al., 2000) or for complex geometry(Schneider et al., 2002). This methodology issummarized through the work flow presented in Fig. 2.The main steps are: the building of the present daygeometry or initial model, the definition of thekinematics, the calibration and the sensitivity analysissometimes followed by the definition of theuncertainties.

Present day geometry. The present day geometryor initial model consists of a 2D cross section or a 3Dblock that represents the state of the sedimentary basintoday. It is built with all the available data (seismic,samples, measurements, field observations, laboratory



data

parameters

present daygeometry kinematics

calibration

sensitivityprediction

uncertainties

Fig. 2. Work flow used in sedimentary basin modelling.

analysis, etc.). At this stage all the traditionalgeological skills such as seismic interpretation,structural geology, sedimentary analysis, andgeochemistry are used (Fig. 3).

Numerical tools are also often used: LOCACE tohelp the structural interpretation (Moretti and Larrere,1989) or DIONISOS to fill the initial model withlithologies (Granjeon and Joseph, 1999).

Kinematics. Once the initial model is terminated,the geological history of the sedimentary basin shouldbe considered. For this purpose, the modeller tries to decipher the past of the considered sedimentarybasin from present day observations and knowledge ofthe geodynamical evolution of the area. Thekinematics reconstruction is a key step. The structuralgeologist is often led to use restoration tools such as



temperature (°C)

porosity (%)

observedcomputed

observedcomputed

observedcomputedhydrostaticlithostatic

observedcomputed

vitrinite reflectance (%) pressure (MPa)

dept

h (k

m)

dept

h (k

m)

dept

h (k

m)

dept

h (k

m)

0 0.5 1.0 1.5 2.0

1

2

3

4

5

60 50 100 150 200

0

1

2

3

4

5

60 10 20 30 40 50

0

1

2

3

4

5

6

0

1

2

3

4

5

60 50 100 150

0

Fig. 4. Example of calibration from well data: in this case values of temperature, pressure, vitrinite reflectance and porosityhave been used.

schneider_f01

0 40 80 120

10

0

km

km

Fig. 3. Example of initial section used in sedimentary basin modelling; colours represent the stratigraphy.

LOCACE or forward kinematics tools such asTHRUSTPACK (Deville and Sassi, 1996). Regarding kinematics deformation, decompaction of the sediments should be accounted for through‘backstripping’ techniques (Perrier and Quiblier,1974).

Calibration. Once the kinematics are achieved andthe physical parameters determined, the firstsimulations can be carried out. The aim of thesesimulations is to adjust the values of physicalparameters in order to make the results of thenumerical model fit the observed data (temperatures,pressures, maturity, etc.; see Fig. 4).

Sensitivity analysis, uncertainties and predictions.The result of the previous step is a set of parametersthat allows us to mimic the observations as well aspossible. It could be useful at this stage to study thesensitivity of the model to small variations of theparameters, which are uncertain. Furthermore, it couldbe compulsory to determine the uncertaintiesregarding some specific results of the numerical modelsuch as the pressure predictions or the chargepredictions.

As the simulation time can be long, too long to useclassical Monte Carlo techniques, a new methodologybased on experimental design method has beendeveloped in QUBS (Wendebourg, 1999).

A now classical use of numerical sedimentarybasin simulators is to calibrate the model in a well-known area and then, after the sensitivity analysis, touse it for forecasting in adjacent areas. Thismethodology has been successfully used to predictpressure in the North Sea (Brigaud et al., 1998).

ConclusionsThe first step during a sedimentary basin study is

to gather and to perform a synthesis of all the existingdata (geological data, geochemical data, structuraldata, mechanical data, thermodynamical data, etc.).This synthesis generally leads to a coherent data setand improves the level of communication between theexperts. Very often, the understanding of thepetroleum system is improved before the very firstcalculations.

The first generation of sedimentary basin modelswas used to understand the petroleum systems inrelatively simple areas. The use of 3D basin modelshas been necessary to perform the first hydrocarbonmass balance (Schneider and Wolf, 2000). At last theprediction of hydrocarbon quality (e.g. composition) is now possible with compositional migration (Béhar et al., 2002). Petroleum systems in complexareas such as foothills can now be studied with 2Dmodels such as CERES (Schneider et al., 2002). Theimprovement of the 3D model and of 3D restoration

algorithms will initiate the building of a newgeneration of sedimentary basin models able toaccount for compositional fluid flow in complex 3Dblocks.

References

Béhar F. et al. (1992) Experimental simulation in a confinedsystem and kinetic modelling of kerogen and oil cracking,«Organic Geochemistry», 19, 173-189.

Béhar F. et al. (1997) Thermal cracking of kerogen in openand closed system. Determination of kinetic parametersand stoichiometric coefficients for oil and gas generation,«Organic Geochemistry», 26, 321-339.

Béhar F. et al. (2002) Rendements compositionnels de genèseet d’accumulation de fluides dans les bassins sédimentaires,Institut Français du Pétrole, contrat G4202/02, rapport56848.

Bouvier V. (1989) Modélisation bidimensionnelle desphénomènes de transport dans les bassins sédimentairespar la méthode des éléments finis, Thèse de doctorat del’École Nationale Supérieure des Mines de Paris, InstitutFrançais du Pétrole, rapport 37606.

Brigaud F. et al. (1998) HP/HT petroleum system predictionfrom basin to prospect scale, European Economic Community,contract OG/211/94-FR-UK, final technical report.

Carruthers D.J., de Lind van Wijngaarden M. (2000)Modelling viscous-dominated fluid transport using modifiedinvasion percolation techniques, in: Geofluids III.Proceedings of the 3rd International conference on fluidevolution, migration and interaction in sedimentary basinsand orogenic belts, Barcelona, 12-14 July, 669-672.

Coelho D. et al. (1996) Temperature, pressure and fluid flowmodelling in Block 330, South Eugene Island using 2D and3D finite element algorithms, in: Proceedings of theAmerican Association of Petroleum Geologists annualconvention, San Diego, 19-22 May, Abstract P A28.

Deville E., Sassi W. (1996) THRUSTPACK. Un logiciel de modélisation intégrée (cinématique, thermique etgéochimique). Application aux Alpes nord-occidentales,«Pétrole et Techniques», 401, 77.

Doligez B. et al. (1986) Integrated numerical simulation ofthe sedimentation, heat transfer, hydrocarbon formationand fluid migration in a sedimentary basin. The Temis model,in: Thermal modelling in sedimentary basins. Proceedingsof the 1st Institut Français du Pétrole exploration researchconference, Carcans (France), 3-7 June 1985, 173-195.

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Faille I. (1992) Modélisation bidimensionnelle de la genèse et de la migration des hydrocarbures dans un bassinsédimentaire, Thèse de doctorat de l’Université Joseph Fourier- Grenoble I, Institut Français du Pétrole, rapport 39553.

Faille I. et al. (1994) Aspects numériques de la modélisationde bassins sédimentaires, Institut Français du Pétrole,rapport 41237.



Faille I. et al. (1996) Finite volume and finite element methodsin basin modelling, Institut Français du Pétrole, rapport43110.

Gerritsen B. et al. (1996) A 3D coupled multi-phase multi-component and thermal simulator for secondary oilmigration, in: Proceedings of the European Association ofGeoscientists and Engineers 58th conference, Amsterdam,3-7 June, Abstract v. 2, L010.

Granjeon D., Joseph P. (1999) Concepts and applications ofa 3D multiple lithology, diffusive model in stratigraphicmodelling, in: J. Harbaugh et al. (edited by) Numericalexperiments in stratigraphy. Recent advances in stratigraficand sedimentologic computer simulations, Tulsa (OK),Society for Sedimentary Geology, 197-210.

Grigo D. et al. (1993) Issues in 3D sedimentary basin modellingand application to Haltenbanken offshore Norway, in: Basinmodelling. Advances and applications. Proceedings of theNorvegian Petroleum Society conference, 13-15 March1991, Stavanger (Norway), 455-468.

Hantschel T., Synofzik H. (1997) 3D basin modelling withfinite elements. Concepts and realisation, in: Proceedingsof the American Association of Petroleum Geologists annualconvention, Dallas (TX), 6-9 April, Abstract P A47.

Hubbert M. K. (1953) Entrapment of petroleum underhydrodynamic conditions, «American Association ofPetroleum Geologists. Bulletin», 37, 1954-2026.

Hunt J. M. (1995) Petroleum geochemistry and geology, NewYork, W.H. Freeman.

Lamoureux-Var V. et al. (1998) Modélisation de la diffusiondu gaz dans les systèmes pétroliers. Étude bibliographiqueet implémentation, Institut Français du Pétrole, rapport44763.

Lerche I. (1990) Basin analysis. Quantitative methods, SanDiego (CA)-London, Academic Press, 2v.

Marle C. (1972) Les écoulements polyphasiques en milieuporeux, Paris, Technip.

Mello U. et al. (1998) New developments in the 3D simulationof evolving petroleum systems with complex geologicalstructures, in: Proceedings of the American Association ofPetroleum Geologists international conference. Rio deJaneiro 8-11 November, «American Association ofPetroleum Geologists. Bulletin», 82, 1942.

Moeckel G. et al. (1997a) Quantification of exploration riskwith 3D integrated basin simulation, in: Proceedings of the American Association of Petroleum Geologistsinternational conference. Wien 7-10 September, «AmericanAssociation of Petroleum Geologists. Bulletin», 81, 1398-1399.

Moeckel G. et al. (1997b) 3D integrated basin simulation andvisualisation, in: Proceedings of the American Associationof Petroleum Geologists annual convention, Dallas (TX),6-9 April, Abstract P A84.

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Perrier R., Quiblier J. (1974) Thickness changes insedimentary layers during compaction history, «AmericanAssociation of Petroleum Geologists. Bulletin», 58, 507-520.

Rudkiewicz J.L. et al. (1997) Development in organicgeochemistry. Geological modelling and impact onexploration issues, Institut Français du Pétrole, rapport44114.

Scheichl R. et al. (2003) Decoupling and block preconditioningfor sedimentary basin simulations, «ComputationalGeosciences», 7, 295-318.

Schneider F. (1989) Modèles numériques de bassinssédimentaires en exploration pétrolière. Revuesbibliographique, Institut Français du Pétrole, rapport 37510.

Schneider F. (1993) Modèle de compaction élastoplastiqueen simulation de bassins, «Revue de l’Institut Français duPétrole», 48, 3-14.

Schneider F., Faille I. (1997) Rhéologie tensorielle poursimulateurs de bassin sédimentaire. Proposition d’une loien vitesse (3D) pour modéliser la compaction des sédiments,Institut Français du Pétrole, rapport 43816.

Schneider F., Hay S. (2001) Compaction model for quartz-ose sandstones. Application to the Garn formation,Haltenbanken, Mid-Norwegian continental shelf, «Marineand Petroleum Geology», 18, 833-849.

Schneider F., Wolf S. (2000) Quantitative HC potentialevaluation using 3D basin modelling. Application to Franklinstructure, Central Grabben, North Sea, U.K, «Marine andPetroleum Geology», 17, 841-856.

Schneider F. et al. (1990) Principes du modèle Themis, InstitutFrançais du Pétrole, rapport 37862, 33.

Schneider F. et al. (1993) Modelling overpressures by effective-stress/porosity relationships in low-permeability rocks.Empirical artifice or physical reality?, in: Basin modelling.Advances and applications. Proceedings of the NorvegianPetroleum Society conference, 13-15 March 1991, Stavanger(Norway), 333-341.

Schneider F. et al. (1994) Modèle de compaction élastoplastiqueet viscoplastique pour simulateur de bassins sédimentaires,«Revue de l’Institut Français du Pétrole», 49, 141-148.

Schneider F. et al. (1996) Mechanical and chemicalcompaction model for sedimentary basin simulator,«Tectonophysics», 263, 307-317.

Schneider F. et al. (1999) Hydraulic fracturing at basin scale,«Oil & Gas Science and Technology», 54, 797-806.

Schneider F. et al. (2000) A 3D basin model for hydrocarbonspotential evaluation. Application to Congo offshore, «Oil& Gas Science and Technology», 55, 3-13.

Schneider F. et al. (2002) Ceres2D. A numerical prototypefor HC potential evaluation in complex area, «Oil & GasScience and Technology», 57, 607-619.

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Frédéric SchneiderInstitut Français du Pétrole

Reuil-Malmaison, France



2.4.3 Planning of exploratory wellsand connected activities

IntroductionWell planning is a very important component of

the exploration and production process and, since itrequires the correct interaction among many differentspecialists within an oil company organization, thisstructured operation is governed by specificprocedures and standards. This process requires theanalysis of both technical and economical factorsconcerning a wide range of local, operational andbudgetary constraints. This operation is, in fact, of acomplexity that demands strong cooperation andintegration among different departments of an oilcompany and, very often, the cooperation of partneroil and service companies.

A well program, which is the document thatrepresents the outcome of this process, is composed ofmany different sections prepared, preferably in anintegrated manner, by different specialists. Of coursethis is the primary document that project teams useduring the execution of a well. The well programdefines, in fact: why the well has been planned; how toconstruct the well in terms of drilling procedures; how,when and what type of well data needs to be acquired;when, how and why the well data must be delivered,analyzed and interpreted.

The main sections of the well program for anexploration and appraisal well (E&A well) are:geological program, drilling program, well dataacquisition program.

Special attention must be paid to the well dataacquisition program since data acquisition andinterpretation have a very strong impact on E&Awells.

The well data acquisition programIt is particularly important to maximize the

relevance of well data in the exploration and appraisalphases, because investment decisions have to be takenwhile the information available is fragile andincomplete. Moreover, when it comes to E&A wells,data acquisition is expensive, and may represent morethan 30% of the total well cost. This means that eachset of data required must be supported by clearobjectives together with a strong understanding of the

ties between data needs, their applications, return, andwell architecture.

Preparing acquisition programs for E&A wellsrequires an excellent understanding of geologicalobjectives (at field scale), well objectives (contingentto the well in consideration), the problems to betackled, and the need for potential developments in thelight of carefully predefined technical and budgetaryconstraints. Often, following an oil company’sproprietary decisional guidelines for well acquisitionplanning and operations, the first effort is devoted toexplicitly pinpointing the key uncertainties and relatedparameters. The second step consists of identifying acritical path leading from the stated uncertainties andparameters to data acquisition techniques geared toreduce them, and to correspond most closely to theexpected well and formation conditions. In fact, wellarchitecture and consequent drilling and technicalcompletion solutions (drilling fluid, drilling methods,well trajectory, bit size, etc.), are the primary source ofconstraints for data acquisition strategies. Whendeveloping a well data acquisition program, wellarchitecture and design are, therefore, matched withthe most appropriate acquisition techniques. Moreover,fall-back solutions for use in the event of technicalproblems, changes to well architecture, or new drillingconstraints, must be anticipated in terms ofpredetermined scenarios.

There are, in general, 7 types of well dataconsidered: a) mud logs; b) solid sampling (cuttings,sidewall cores, cores, etc.); c) while drilling logs;d ) well seismic; e) wire line logs (both open and casedhole); f ) fluid sampling; g) well testing.

The well data acquisition program should also beprepared in the light of the information system usedto share the data and feed the proprietary databasefor subsequent studies. The contractual context alsoprovides evidence of the value of the informationrequested, not only regarding its cost but, even moreimportantly, in terms of return of investment orfurther cost savings on the acquisition of other typesof data.

Well and surface seismic data are the main sourcefor updating knowledge and matching the models of agiven geological object. Thanks to the hard data theyprovide, the wells are the only points of direct control,and the reservoir’s geological model must honour the



well data acquired. The type and quality of the data arekey issues for the understanding of characteristics andfeatures of the geological object under consideration,and for the quality and reliability of the results of theupcoming studies in many different disciplines(structural geology, stratigraphy, sedimentology,petrography, geochemistry, seismic interpretation,petrophysics, geomechanics, etc.).

The objectives targeted in drilling E&A wells areto understand the geological object, and to prepare andanticipate the needs of the potential developmentphase. It is also important, in an early explorationphase, to identify the key uncertainties to be solvedwith the development phase in view. Formationevaluation measurements and samples should beidentified, justified and acquired as early as possible.Adequate procedures for a post mortem evaluation ofthe quality and suitability of the data acquired, thequality and reliability of the results of theinterpretation phase, and the cost and value of theinformation acquired, should be adopted within thisprocess. This ensures the feed-back necessary toimprove the acquisition, processing and interpretationstrategies of well data for further wells to be drilled inthe field. The results of this post mortem assessmentcan help to maximize well data utilization, and toreduce the acquisition costs in the late stages of filedappraisal and developments. Care is usually given toimportant aspects of HQSE (Health, Quality, Safetyand Environment) issues, in accordance with more andmore stringent HQSE company polices.

The well programAccording to the above-mentioned procedures and

information, this document is, generally, composed ofseveral different sections. The main ones are: a)general information section; b) geological section; c)operational geology section; d) drilling section.

General information sectionThis section also consists of various subsections,

including: a) well data (well name, type of well, totaldepth, permit, operator and partnership information,etc.); b) well objectives; c) topographical data(latitude, longitude, ground elevation level for onshorewells, relevant topographical information, etc.);d) general recommendations; e) general informationabout the drilling rig and related safety features;f ) emergency information and emergency workflowplan; g) measurement units in use; h) main drillingprognoses (Fig. 1); i) well sketch.

Geological sectionThe geological section of a well program is mainly

composed of the following chapters: a) well location

(latitude, longitude, other relevant topographicalinformation, etc.); b) geological setting of the area ofinterest; c) seismic interpretation; d) well targets(seismic reference line, description of main geologicaltargets with reference to reservoir types and lithology,expected petrophysical and geological characters,expected depth of the main target tops, etc.); e) sourceand cap rocks; f ) lithological and stratigraphicalprognoses; g) reference wells.

Operational geology sectionThe main subsections of this section are: a) surface

logging with relevant information about theacquisition and quality control of mud logging data tobe reported in a daily geological report and in themaster log document; b) relevant information aboutfluid and solid sampling (gases, cuttings, bottom andsidewall coring, formation fluid sampling, etc.);c) well log acquisition with information about thedesigned logging suites (both for drilling and wire linelogging) and expected operational conditions (nominalborehole sizes, mud data information such as mudtypes and density, etc.); d) well seismic research;e) wire line and/or formation testing; f ) well datainterpretation products.



0 20 40 60 80 100 120 140 160

time schedule (days)

mea

sure

d de

pth

(m)

drilling phase 23"

drilling phase 16"

drilling phase 12 1/4"

drilling phase 8 1/2"

job casing 18 5/8"

job casing 13 3/8"

log�job casing 9 5/8"

log�job liner 7"�well testing

4,000

0

500

1,000

1,500

2,000

2,500

3,000

3,500

Fig. 1. Schematic time schedule diagram.

Drilling sectionThe drilling section is often composed of the

operational drilling program chapter and the welldesign chapter. The operational drilling programprovides: very detailed operational information foreach drilling phase; details about drilling proceduresand safety issues; selected bit types; bottom holeassembly composition; selected mud types; type,weight and setting of casing; cementing; relevantinformation about formation and well testing; plannedcompletion scheme and settings; contingency plansand well data acquisition activities.

In order to plan the well design and related drillingtechniques effectively, a wide range of information isrequired. The most relevant regards the expectedpressure gradients (specifically, the overburdengradient, the pore pressure gradient, the fracturationgradient and the temperature profile as presented inFig. 2). This information is generally derived from theanalysis of drilling reports and well data acquired innearby reference wells. Open hole well logs, availablewire line formation testing data, and the results of thegeological and petrophysical interpretation of welllogs, are all particularly important aspects of the welldata in terms of evaluating pressure profiles. This isespecially true concerning anomalous pressures(mostly overpressures) or the presence of densityprofile anomalies related to peculiar lithology profilesand fluid distribution (e.g. shallow gas), particularlyhazardous in the case of deep water exploration wells.When this well data is not available, the necessaryinformation is inferred from regional geologicalknowledge.

Other very important elements of a correct wellconstruction design are related to the geological andgeomechanical characteristics of the stratigraphicsequence. Well bore instability problems are, in fact,mostly related to the petrophysical properties of therock, and to lithology - e.g. instability of shales in thecase of water-based muds, due to the presence ofspecific clay minerals whose swelling may causecaving, torque, over-pulling and drill string sticking. Agood understanding of the lithological, petrophysicaland mechanical properties of all the geologicalformations present in the predicted stratigraphicsequence (both target and cap rock formations), isfundamental to the correct selection of drilling bits(type and size), mud type and weight, casings (size,weight and depth), drilling procedures andtechnologies.

Further important components of the drillingprogram are the mud and cementing programs. Themud program provides information about the typesand characteristics of the mud systems selected forthe different sections of the well, the drilling mud

consisting in a mixture of one or two liquid phasesand dissolved and undissolved solids with propertiestailored to solve a number of particular problems.The presence of a drilling mud is, in fact, necessaryto cool and lubricate the drilling bit, to condition theformation wall, to remove cuttings from theborehole, and to bring traces of formation fluids tothe surface. When the mud possesses certaincharacteristics, it provides a well bore mediumsuitable for certain kinds of electrical, acoustic andnuclear well logging measurements. The main typesof mud are Water Based Mud (WBM) and Oil BasedMud (OBM). The main mud characteristics are mudtype, density, viscosity, pH, salinity, weight, volumeof solids, filtrate volume, etc. Also of greatrelevance are the estimated mud volumes as afunction of the excavated hole volume (evaluated byusing specific caliper log measurements, such as theborehole geometry tools or borehole televiewers),and the expected casing volume as a function ofcasing size and weight. In relation to thesepredictions, reference is made to well site stocks in



0 50 100 150 200 250 300temperature profile (°C)

gradients [(kg/cm2)/10 m]

overburden gradientpore gradientfracturation gradienttemperature

0

500

1,000

1,500

2,000

2,500

3,000

3,500

0 0.5 1 2.521.5 3

dept

h (m

)

Fig. 2. Predicted pressure gradients and temperature profile.

terms of type and volume of products, quality andtype of use.

The cementing program provides informationabout the types and characteristics of the cementsselected for the different sections of the well.Cementing consists in the application of a liquidslurry of cement and water to various points inside oroutside the casing. This aims to fill the annulusbetween the casing and the formation with cement tosupport the casing, improve zonal isolation, orprevent the migration of fluids between permeablezones by ensuring the adherence of casing to cementand cement to formation. When casing is run in awell, it is set, or bonded, to the formation usingcement. The selected cement type, additives, water

salinity and expected slurry volumes are all of greatrelevance to this procedure. Again, in relation tothese predictions, reference is made to well sitestocks in terms of type, quality and volume ofproducts, and type of use.

Bibliography

Louis A. et al. (2000) Well data acquisition strategies, in:Proceedings of the Society of Petroleum Engineers annualtechnical conference and exhibition, Dallas (TX), 1-4October, SPE 63284.

Mauro GonfaliniScientific Consultant



Documents

2.4 Evaluation and development of the exploration