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7/28/2019 2D Basin Modeling and Petroleum System (Okui, 1997)
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PA97 - PO - 15
INDONESIAN PETROLEUM ASS0CIATION
Proceedings of the Petroleum Systems of SE Asia and Australasia Conference, May 1997
K EY TO SUCCESSFUL PETROLEUM SY STEM ANAL Y SIS :UNDERSTANDINGOF INPUT PARAMETERS IN 2D BASIN MODELING
AkihikoObi*
HNTRODUCTION
Basin modeling techniques are giving new insights to
oil and gas exploration, since they can integrate many
processes with quantitative evaluation on the historyof sedimentary basins (Figure I). Many geological and
geochemical processes are too slow and compies for
human beings to integrate quantitatively. But the
evolution of computer techniques enables us to
simulate and visualize these processes in human time
and space scales.
Explorationists generally develop several hypotheses
or scenarios during evaluations. The artificial
experiment nE basin modeling can compare these
hypotheses. Since each module forming the whole
basin modeling package is developed through physicaland chemical knowledge, basin modeling can provide
constraints and reality checks on these hypothesis and
hence reduce exploration risk.
Quality, accuracy and reality of the simulations
depend not only on the model itself, but also on input
parameters and the numerical scheme. In this paper, I
woulcl 1 c': !o discuss pitfalls in 2D basin modeling.
Successful modeling can be only accomplished by the
tuning of input parameters with geological
understanding, not by using default values in
commercial software packages.
In this paper, the properties of shale (such as
permeability, relative permeability, capillary pressure),
and the kinetic parameters for source rocks are
discussed.
METHODS
The modeling in this paper was conducted by JNOC's
* Japan National Oil Corporation
two-dimensional three-phase fluid flow basin
modeling, "SIGMA-2D" (Okui et al., 1994, 1996).
SIGMA-2D (2-Dimensional Simulator for Integration
bf Generation, Migration and Accumulation) is a finite
difference code developed by the TechnologyResearch Center of Japan National Oil Corporation.
SIGMA-2D can simulate the generation, migration
and accumulation of oil and gas (three-phase fluid
flow) in a two-dimensional cross section (Figure 2).
The modeling is divided into three categories;
Geological, Generation and Migration (Figure 3).
The geological modeling is responsible for the
reconstruction of burial and compaction of sediments,
tectonic and hydraulic fracturing, fluid flow and heat
flow. Compaction is calculated based on effective
stress law and fluid flow condition, which is governedby Darcy's law. Pressure increase is achieved either
by sediments loading, fluid expansionorhydrocarbon
generation. Tectonic fracturing is calculated by
simplified strain'analysis and hydraulic fracturing is
predicted based on pore pressure distribution.
Conductive and convective heat flow creates the
temperature distribution in the section.
The generation modeling is responsible for the
calculation of maturation of organic matter (vitrinite
reflectance and sterane epimerization) and generation
of oil and gas. A first-order kinetic reaction model isapplied for these calculations and multiple parallel
reactions are used for the generation.
The migration modeling is responsible for the
calculation of expulsion, secondary migration, PVT
condition (dissolution of fluid) and sealing
(accumulation). Expulsion and secondary migration is
calculated based on Darcy's law using relative
permeability concepts. Maximum dissolved capacity
of gas into oil is calculated based on pressure and
913
© IPA, 2006 - Proceedings of an International Conference on Petroleum Systems ofSE Asia and Australasia, 1997
sc Contents
Contents
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914
temperature for certain oil and gas types. Free gas
which corresponds to the excess of this capacity can
migrate as a separate phase. Migrating oil and gas can
be trapped based on capillary pressure concepts.
Four governing equations with the terms related toabove phenomena are solved simultaneously in each
time step at each grid point in the section (Figure4).These equations are mass conservation equations for
water; oil and gas, respectively, and an energy (heat)
conservation equation. Rock and fluid properties have
to be given as input parameters. The rock properties
related to fluid flow such as permeability, relative
permeability and capillary pressure are primarily given
as a function of porosity for each lithology. The
properties related to heat flow such as thermal
conductivity and heat capacity are given as a function
of porosity, temperature and pressure.
SIGMA-2D has been applied to over 25 basins
throughout the world, mainly to basins in Japan and
Asia, but also to these in the North Sea and Middle
East.
RESULT S AND DISCUSSION
VitriniteReflectance
Simulation of hydrocarbon generation requires
assumptions regarding the thermal history in a basin.
Thk thermal history is generally calculated by
basement heat flow, surface temperature and thermal
conductivity of rocks in basin modeling (Waples et
al., 1992). Basement heat flow is so sensitive to
thermal history that it is usually calibrated by
measurable parameters. For present heat flow, actual
temperatures recorded at wells during electrical
logging or testing are used. Maturity indicators such
as vitrinite reflectance are used for the calibration of
paleo-heat flow, since it increases as a result of the
sum of heat energy from past to present.
Relatively low vitirinite reflectances compared to high
geothermal gradients are widely observed in Southeast
Asia. This combination results in low paleo-heat flow
with a rapid increase since Pleistocene to the present.
This spiky heat flow suggests an activation of rifting
since Pleistocene, which can not be geologically
justified.
Fluorescence alteration of multiple macerals (FAMM)
analysis (Wilkins et al., 1992, 1995) is a method to
measure fluorescence alteration of various macerals
without considering the type. The results can be
converted to true vitrinite reflectance by the cross-
plots of the degree of the alteration against the
intensity, since the relationship for standard vitrinitewas established. The advantage of this method is to
eliminate the uncertainties of identifying macerals in
conventional vitrinite-reflectance measurements, such
as skill of the technician, cavings and reworking. The
effect of chemical composition on the reflectance can
also be eliminated.
FAMM analysis on the samples from Southeast Asia
indicated that many vitrinite-reflectance measurements
appear to be suppressed (Waples et al., 1997). The
combination of a vitrinite-reflectance profile suggested
by FAMM analysis with temperature measurementsjustify an exponential decay or high constant
basement heat flow, which is more consistent with the
geological setting in Southeast Asia. The importance
of this is that modified thermal history calculates
earlier generation of oil and gas. In the Khmer Trough
of Cambodia, the difference is about eight million
years, which allows vertical oil migration for 800m
even if the flow rate is as low as m/year. (Okui
et al., 1997).
K inetic Parruneten
Oil generation occurs as a degradation of kerogen and
gas generation mainly occurs as a degradation of oil.
Most basin modeling software packages adopt first-
order parallel reactions to express these processes
(Tissot et al., 1987; Ungerer, 1990). Each reaction is
described by reaction kinetics in this model and the
kinetic parameters include activation energy and
frequency factor. The activation energy is the energy
required to activate the reaction and may vary
according to the strength of a bond in chemical
compounds. Since various chemical compounds
construct a kerogen, the activation energies are given
as a distribution for each type of kerogen (Tissot et
al., 1987; Ungerer, 1990). It is expected that the
activation energy distribution in source rock varies
according to the type of organic matter and
depositional environment.
About three hundreds measurements of kinetic
parameters in the Akita Basin of J apan indicate that
the activation energy distribution varies even within a
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915
marine Type I1 kerogen. Kerogen with more sulfur,
nitrogen and oxygen content exhibits a lower and
wider distribution, which is interpreted by the
assumption that these elements are expected to
weaken the chemical bonds in the kerogen. Source
rock with lower activation energy distribution isrecognized at the basin margin where high organic
'productivity and an anoxic environment due to
upwelling are suggested.
A simulation in the Akita Basin applying a lower
activation energy distribution for the marine Type I 1kerogen indicates earlier initiation of oil generation
even though the peak is not much different from the
conventional Type11 Earlier initiation of generation
may allow oils to migrate further in a basin.
KineticParameters for Coal
Kinetic parameters are generally derived from the
result of pyrolysis experiments such as hydrous
pyrolysis and rock-eval pyrolysis. In this type of
experiment, high temperature is generally applied to
compensate for the time required to generate
hydrocarbon. Moreover, the rock-eval is generally
conducted under an open system. These conditions
force the hydrocarbon generated in the experiment to
be expelled out of the source rock sample, since the
viscosity of generated hydrocarbon becomes very low
due to high temperature.
Pepper (1 991) and Pepper and Corvi (1 995) suggested
that the initial oil generated, especially in coals,
should be adsorbed in a kerogen, maybe due to
polarity of the oil. The adsorbed oils will be cracked
to gas by additional heating with burial and. expelled
as gas phase. I t is difficult to reproduce the adsorption
phenomena by any pyrolysis experiment. Therefore,
the activation energy distribution derived from these
experiments should be used with caution, especially
for coals.
Pepper (1991) proposed maximum adsorption capacity
as 200 mgHC/gTOC. Therefore, one of the methods
to apply the activation energy distribution from the
experiments is to take 200 mgHC/gTOC from the
lower part of the distribution and add them above the
activation energy corresponding to the oil cracking
range, which enables gas generation directly from the
kerogen. The application of such a modified activation
energy distribution to a basin in Southeast Asia
indicated that much more gas is generated and
migrated, which is consistent with the distribution of
gas fields in that basin.
Absolute Permeability for Shale
Absolute permeability is a principal rock property
which controls fluid flow in a basin. This property is
generally described by the Kozeny-Caman equation,
which indicates that the permeability decreases as
porosity decreases. Since the Koreny-Carman equation
was derived from the theoretical consideration of
repacking of spheres, this should be keep in mind
when applying to rocks that have suffered chemical
diagenesis.
SIGMA-2D's application in the Akita Basin of Japan
revealed that the Kozeny-Carman equation for shalecan not reproduce existing overpressuring in this
basin. More rapid decreaseofpermeability is required
to simulate the overpressuring in this basin, which is
interpreted as being due to diagenetic cementation of
zeolite and quartz in the throats of pore system. Itwas
found that the overpressured rocks contain more
zeolite and quartz than clay; these minerals were
originally deposited as volcanic glass and diatoms in
deep marine environments, respectively.
Relative Permeability for Shale
Relative permeability is a convenient rock property to
model multi-phase fluid flow in a basin. Laboratory
measurements can be done on reservoir rocks, but not
on fine-grained rocks. The analogue of reservoir rocks
is generally applied for fine-grained source rock and
seal rock in 2D basin modeling.
SIGMA-2D's application in the North Sea revealed
that the analogous curve can not reproduce enough
expulsion of oil and gas, and hence enough
accumulation confirmed by drilling. For medium to
lean source rock, it becomes more serious, as
demonstrated by the application to the Niigata Basin
of Japan.
It was found that only the curve with high irreducible
water saturation can simulate a consistent result (Okui
and Waples, 1993). This new curve was predicted by
careful examination of various curves from reservoir
rocks. It was suggested that fine-grained rocks contain
much more irreducible water due to micro-porosity
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916
and bonded water at the surface of grains and thereby
it is required to fill most of pore space with oil to
create dominant oil flow.
In the North Sea simulation, this new curve
successfully simhated downward expulsion of oilfrom Upper Jurassic source rocks (Draupne and
Heather Formations) to Middle Jurassic carrier beds
(Brent Formation). The contribution &om both source
rocks to charged volumes in traps was consistent with
biomarker composition in this simulation.
Capillary PRSSUR or Shale
Capillary pressure plays an important role €or sealing
oil and gas in a basin. This rock property is primaly
given as a function of pore-throat size. Since the
throat size decreases as compaction proceeds, sealingcapacity (capillary pressure) should be given as a
function of depth (or porosity).
If a trap receives oil at shallower depth, the leaking of
oil can start earlier, resulting in a shorter oil column.
For fine-grained seal rock, as well as source rock, it
is also not necessary to fill most of pore space with
oil. This combination simulated the leaking of oil
from Middle Jurassic reservoirs to the Tertiary for the
North Sea application.
A nhydnte
Anhydrite is generally considered as a complete seal,
for which very low permeability is given. SIGMA-
2D's application to the Middle East indicated that very
low permeability for anhydrite seals caused the
dipping of the oil/water contact of an accumulation
due to strong waterflow in horizontal direction, which
is not consistent with the actual distribution of oil.
Careful observation of an anhydrite core revealed that
a network of dolomitic mudstone exists in the
anhydrite, showing chicken-wire structure. Mercury
injection tests on this anhydrite indicated that the
pore-throats of this network were large enough to leak
water. A new application, given higher permeability to
the anhydrite bed, demonstrated a relatively flat
oillwater contact, which is consistent with reality.
Furthermore, the simulation indicated that oil can
migrate vertically through anhydrite beds before
severe compaction.
CONCLUSIONS
Two-dimensional basin modeling is one of the best
tools to evaluate the petroleum system. Since basin
modeling is a computer simulation technique, not only
the models but also the input parameters determinethe accuracy of the evaluation. However, existing
commercial software packages only supply
generalized default values. Therefore, the users have
to be careful to apply these values directly, and the
tuning of the input parameters with understanding of
those background is a key to successful two-
dimensional basin modeling.
REFERENCES
Okui, A . and Waples, D.W., 1993, Relativepermeability and hydrocarbon expulsion from source
rocks, In : A.G. Dore et al. (eds), Basin Modelling :
Advances and Applications, Elsevier, 293 -301.
Okui, A ., Hara, M., Fu, H. and Takayama, k.,1996,
SIGMA-2D : A simulator for the integration of
generation, migration, and accumulation of oil and
gas. Proceedings of VIIIth International Symposium
on the Observation o€the Continental Crust Through
Drilling, 365-368.
Okui, A,, Hara, M. and Matsubayashi, H., 1994, Theanalysis of secondary migration by two-dimensional
basin model "SIGMA-2D" (abstract), 1994 AAPG
Annual Convention Official Program, 227-228.
Okui, A,, Imayoshi, A. and Tsuji, K., 1997, Petroleum
system in the Khmer Trough, Cambodia, this volume.
Pepper, A.S., 1991, Estimating the petroleum
expulsion behaviour of source rocks: a novel
quantitative approach. In : England, W.A. and Fleet,
A . . (eds) Petroleum migration, The Geological
Society, Special Publication, 59, 9-31.
Pepper, A S. and Corvi, P.J ., 1995, Simple kinetic
models of petroleum formation. Part 111: Modelling an
open system, Marine Petrol. Geol. 12, 417-452.
Tissot, B., Pelet, R. and Ungerer, B., 1987, Thermal
history of sedimentary basins, maturation indices and
kinetics of oil and gas generation, Bull. Am.
Assoc. Petrol. Geol. 71, 1445 -1466.
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917
Ungerer, P., 1990, State of the art of research in
kinetic modelling of oil formation and expulsion,Org.Geochem. 16, 1-25.
Waples, D.W., Suizu, M., and Kamata, H., 1992, The
art of maturity modeling, Part2: Alternative modelsand sensitivity analysis, Bull. Am. Assoc. Petrol.
Geol. 76, 47-66.
Waples, D.W., Ramly, M . and Leslie, W., 1997,
Implication of vitrinite-reflectance suppression for the
tectonic and thermal history of the Malay Basin,
Proceedings Volume Kuala Lumpur 1994 AAPG
International Conference -- Southeast Asian Basins:
Oil and Gas for 21st Century, Kuala Lumpur,
Geological Society of Malaysia, (in press)
Wilkins, R.W.T., Wilmshurst, J.R., Russell, N.J.,Hladky, G., Ellacott, M.V. and Buckingham, C.P.,
1992, Fluorescence alteration and the suppression ofvitrinite reflectance, Org. Geochem. 18, 629-640.
Wilkins, R.W.T., Wilmshurst, J.R., Hladky, G.,Ellacott, M.V. and Buckingham, C.P., 1995, Should
fluorescence alteration replace vitrinite reflectance as
amajor tool for thermal maturity determination in oil
exploration?, Org. Geochem. 21, 191-209.
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FIGURE 2 - Three Phase Fluid Flow System. SIGMA-2D can simulate the generation, migration andaccumulationof oil and gas (three-phase fluid flow) in a two-dimensional cross section.
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PRINCIP
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921
- GAS GENERATIONby KINETIC MODEL- GAS EXPANSION & COMPRESSION- MAXIMUM DISSOLUTION OF GAS IN OIL
- RELATIVE PERMEABILITY for GAS- CAPILLARY PRESSUREOf GAS- GAS FLOWby DARCY'S LAW
STRUCTURE OF S IGMA-ZDMASS CONSERVATION OF WATER MASS CONSERVATION OFOIL
- COMPACTIONof SEDIMENTS- WATER EXPANSION&COMPRESSION
- FRACTURING- POROSITY REDUCTION- PERMEABILITY CHANGE- RELATIVE PERMEABILITY forWATER- WATER FLOWby DARCY'S LAW
ItMASS CONSERVATION OF GAS
~- OIL GENERATIONby KINETIC MODEL- OIL EXPANSION & COMPRESSION
- DENSITY & VISCOSITY OF OIL
- RELATIVE PERMEABILITY for OIL- CAPILLARY PRESSUREof OIL
- HC FLOWby DARCY'S LAW
- CONDUCTIVE HEAT FLOW- CONVECTIVE HEAT FLOW
- VlTRlNlTE REFLECTANCE
- STERANE EPIMERZATION
+-F IGURE4 - Structure of SIGMA-2D. Four governing equations with the terms related to above
phenomena are solved simultaneously in each time step at each grid point in the section.