ORIGINAL PAPER

3-D predrill overpressure prediction using prestackdepth-migrated seismic velocity in a fieldof southwestern Malay Basin

Iftikhar Ahmed Satti & Deva Ghosh &

Wan Ismail Wan Yusoff

Received: 29 September 2014 /Accepted: 19 November 2014# Saudi Society for Geosciences 2014

Abstract Quantitative predrill pore pressure prediction isvery important for reducing the drilling hazards. In manyTertiary basins, generation of overpressure is mainly by com-paction disequilibrium due to high deposition rate and lowpermeability in shale. In the Malay Basin, high geothermalgradient (i.e., 40–60 °C/km) and high heat flow also play animportant role in generating overpressure at shallow depth.This study describes the utilization of 3-D prestack depth-migrated seismic interval velocity for predrill pore pressureprediction in a field of southwesternMalay Basin. The qualityof 3-D prestack depth-migrated seismic interval velocity wasenhanced by calibration with check-shot data. ModifiedGardner’s equation was used to generate the 3-D density cubefrom the interval velocity. The Eaton and Bowers methodswere used to compute and predict pore pressure values fromthe seismic velocity. The Eaton method with standard expo-nent for seismic velocity gave good prediction in the shallowerzone where overpressure is caused by undercompaction mech-anism, whereas underpredicted the high pore pressure at thegreater depth where fluid expansion is the cause of overpres-sure. However, the overpressures were predicted quite well byapplying correction on the Eaton method for fluid expansionmechanism.

Keywords Overpressure . Interval velocity . Anisotropy .

Depth migration . Prediction

Introduction

Pore fluid pressure higher than the normal/hydrostatic pres-sure is called overpressure and has significant importance ingeohazards analysis and prediction (Bowers 2002). In the highoverpressured regions, accurate predrill pore pressure predic-tion is very important for casing point selection and wellplanning. Pore pressure prediction has implication in migra-tion modeling for prospect evaluation and seal prediction.

Undercompaction and fluid expansion are two most com-mon mechanisms of overpressure generation. Different porepressure prediction schemes are required for both mecha-nisms, as they have different effect on rock properties(Tingay et al., 2009). The undercompaction mechanism oc-curs when low permeability prevents the rapid escape of porefluids due to fast deposition. Fluid expansion (unloading)mechanism such as aqua thermal expansion, kerogen to gasmaturation, and clay digenesis can increase pore fluid volumewithin the confined pore space (Bowers 2002). In case of fluidexpansion mechanism, pore pressure increases more rapidlythan the lithostatic pressure, so fluid expansion can decreasethe effective stress (Bowers 2002).

Undercompaction is the main mechanism of overpressuregeneration in most of the Tertiary sedimentary basins wheresedimentation rate is high. Other mechanisms such as chem-ical compaction and fluid expansion can generate overpres-sure in the deeper part of the sedimentary basins (Deminget al. 2002). For pore pressure prediction, it is importantto understand the different mechanisms of overpressuregeneration and their effect on rock properties (Swarbrick2001). Seismic velocity is most reliable tool for predrillpore pressure prediction in the frontier area. Pennebaker(Pennebaker 1968) first demonstrated the concept ofusing seismic interval velocity for pore pressure predic-tion. Seismic pressure prediction relies on detectingchanges in interval velocity with depth. These changes

I. A. Satti (*) :D. Ghosh :W. I. Wan YusoffDepartment of Geosciences, Universiti Teknologi PETRONAS,Perak, Malaysiae-mail: iasatti@gmail.com

Arab J GeosciDOI 10.1007/s12517-014-1734-y

reflect the properties of the overpressured rocks, which,in most cases, are undercompacted (Dutta 2002).

Mechanical compaction due to sedimentation increases theeffective stress and reduces the porosity with depth. Seismic P-wave velocity has direct relation with effective stress andincrease with depth due to increase in effective stress.However, if the rate of sedimentation is very high and fluidcannot escape from the pore space due to low permeability inrock, pore fluid will support a part of the overburden andbecome overpressured. As overpressure reduces the amountof compaction that could occur, seismic velocity can be usedfor pore pressure prediction (Sayers et al. 2006). According toChopra and Huffman 2006, accuracy of the seismic velocity isone of the key factors required for reliable pore pressure pre-diction. The quality of the seismic velocity could be improvedusing advanced seismic processing techniques like high-densityhigh-resolution velocity analysis, prestack seismic simulta-neous inversion, and anisotropic prestack depth migration etc.In this study, we used anisotropic 3-D prestack depth-migrated(PSDM) seismic velocity for predrill overpressure prediction.

Geological history of the Malay Basin

TheMalay Basin is situated to the east of PeninsularMalaysia,in the South China Sea (Fig. 1). Malay Basin is a NW-SE

trending rift basin geometrically asymmetric in form withthe depositional axis occurring closer to the southwesternflank of the basin (Ebdale and Redfern 1997). The sed-imentary history of the Malay Basin began in the LateEocene-Early Oligocene (45 Ma). Malay Basin has twodepositional episodes: (i) syn-rift with continuous subsi-dence including thermal and (ii) post-rift with basininversion in Middle-Late Miocene (Ghosh et al. 2010).Sedimentary sequence in the Malay Basin is subdividedinto different stratigraphic groups starting from the A(Recent) to the M (Oligocene) (Ghosh et al. 2010).

The study area is located in the southwestern part ofthe Malay Basin, and it comprises an elongated NW-SEtrending anticline. This anticlinal structure is dissectedby a series of broad north-south trending normal faults.Normal faults have en echelon arrangement, which sug-gest the presence of shear component in the westernflank of the study area (Ebdale and Redfern 1997).

Based on structural interpretation, the study area can bedivided into four clearly defined fault blocks (Fig. 2). Themain fault block A is not significantly affected by normalfaulting and is tested by seven wells, while fault blocks Band C (shear zone ) are structurally more complex due to thepresence of many extensional faults and are tested by twowell. The fault block D is on the western side of the study areaand is tested by one well.

Fig. 1 Location map of theMalay Basin and study area,modified from (Tjia and Liew1996)

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Overpressure in the Malay Basin

The Malay Basin is one of the most prolific hydrocarbon-producing basins in Southeast Asia. Overpressure developedin the deeper parts of the basin due to the deposition of 12-kmfine-grained Tertiary sediments during the last 35 Ma (Hoesniet al. 2003). The depth to the start of overpressure variesacross the Malay Basin. The top of overpressure is shallowerin the basin center (i.e., 1.9–2.0 km) and gradually deepenstoward the basin flanks (i.e., 3.0 km) as shown in Fig. 3(Hoesni 2004).

The top of overpressure does not conform to any particularstratigraphic group. There exists no relationship between thetop of overpressure and the temperature distribution in theMalay Basin. A previous study (Koch et al. 1994) has shownthat overpressure is not generated by undercompaction alone.

Fluid expansion or unloading mechanisms may have alsocontributed to the high overpressure in the Malay Basin.

Temperature may also play an important role in thedevelopment of overpressure. Geothermal gradient is high(i.e., 50 °C/km) in the central Malay Basin resulting in thinand shallow dewatering zone. This may probably be thereason for the occurrence of stratigraphically younger unitsat shallow depth. While toward the basin flanks, geothermalgradient is less and overpressure occurs deeper in older strat-igraphic units (Shariff and Leslie 1995).

Malay Basin is characterized by high heat flow with geo-thermal gradient of between 40 and 60 °C/km that has influ-ence on hydrocarbon generation and migration (Yusoff 2011).There is a strong correlation between the rate of sedimentationand the overpressure development by disequilibrium compac-tion. However, when wells are drilled deeper into the basin,

Fig. 2 Example of an interpreted horizon showing the presence of extensive normal faulting in the study area. The locations of fault blocks and wellsused for pressure prediction validation are also shown

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thermal processes in shale will result in secondary overpres-sure generation (O’Connor et al. 2012). It suggests that addi-tional overpressure mechanisms such as clay mineral diagen-esis and active hydrocarbon generation exist in the MalayBasin.

Overpressure in the study area

Study area is situated in the southwestern Malay Basin whereoverpressure behavior is variable, with different fault blocksshowing different overpressure trend. Overpressure may startdeeper and ramp up rapidly or start at shallow and ramp upgradually with depth. Overpressure is observed in almost allof the wells drilled in the study area. Pore pressure dataobtained from well test tools such as repeat formation tests(RFTs), drill stem tests (DSTs), and modular formation dy-namics tests (MDTs) was used to analyze the overpressuredistribution.

In the study area, heat flow is up to 75 mW/m2 causingsource rock to mature at earlier and hydrocarbon generationstart at shallow depth. This can also contribute to overpressuregeneration (Satti et al. 2013). According to the recent study inthe area (Satti et al. 2014), overpressure in the shallower zoneis caused by undercompaction, whereas in the deeper zone,fluid expansion is the mechanism of overpressure generation.

3-D seismic velocity processing

3-D PSDM seismic interval velocity data used for pore pres-sure prediction. The processing workflow of the seismic ve-locity is shown in Fig. 4.

The initial velocity model was constructed by using thesecond pass anisotropic migration velocity picked at densegrid of 100 m×100 m. The constructed root-mean-square(RMS) velocity was converted to interval velocity (vint) andfurther converted to depth domain.

Fig. 3 The onset of overpressure in Malay Basin (Hoesni 2004). The depth to the start of overpressure is shallowest in the basin center and increasesgradually toward the basin flanks. The top of overpressure crosscuts the stratigraphy of the basin

Fig. 4 Processing workflow

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Fig. 5 Final migration model before well calibration

Fig. 6 Final migration model after well calibration

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The initial interval velocity model was updated in sixiterations. The updated model obtained from iteration 1 wasused in beam prestack depth migration to produce a set of25 m×25 m grid of common image point (CIP) gathers.Iteration 5 involved mechanically slowing down the velocitiesaround the affected faults and bull’s-eye. Velocity scanningusing various percentages of velocities was carried out beforearriving at an optimal percentage to use in slowing down thevelocity. This test was repeated for every area that requiredadjustment. High-resolution tomography update was then per-formed. In iteration 6, anisotropy update was carried out byusing the delta model to depth adjust the iteration 5 velocitymodel to obtain a vertical velocity model. After validating thetomography update, this velocity model was used for the finalanisotropic Kirchhoff depth migration.

The final velocity model obtained after applying anisotrop-ic Kirchhoff depth migration was calibrated with the well topsand two interpreted depth surfaces. The model was iterativelyupdated by reducing the depth difference between theinterpreted horizons and well tops. The brief description ofthe workflow used for well calibration is discussed below.

The supplied depth surfaces were being scaled to verticaltime through the final imaging interval velocity volume. Theinterval velocity volume, used to produce the final depthimage, was converted to its corresponding average velocitytime. Analysis of the well ties with the supplied interpretationwas used to calculate a multiplication factor or scalar at eachwell location, which were spatially mapped. The scalar mapswere used to create the scalar volume which was utilized tocalibrate the average velocity volume. The calibrated averagevelocity volume was then converted back to its correspondinginterval velocity. The time interpretation from average veloc-ity was scaled back to depth through the calibrated intervalvelocity volume. Analysis of the well ties with the calibrateddepth surfaces was carried out to determine if the differenceswere sufficiently reduced. Example of velocity before andafter calibration with wells is shown in Figs. 5 and 6,respectively.

3-D seismic velocity modeling

The quality of interval velocities derived from seismic pro-cessing has direct impact on the accuracy of pore pressureprediction. Interval velocity extracted from 3-D cube for dif-ferent well locations was compared with the check-shot/sonicvelocity to check the accuracy of the seismic velocity. In mostof the wells, seismic velocity was slightly lower than thecheck-shot/sonic velocity (Fig. 7a).

3-D grid-based velocity modeling technique of Petrel soft-ware was used to refine the PSDM interval velocity cube bycalibrating with the check-shot interval velocity from the

Fig. 7 a Comparison of sonic/check-shot velocity with seismic velocitybefore and after calibration with check-shot velocity at blind welllocation. Seismic velocity density is showing better match with thesonic velocity after check-shot calibration. b Final PSDM intervalvelocity cube obtained by calibration with check-shot data from theoffset wells. This is the calibrated velocity used for density calculationand pore pressure prediction

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offset wells. The summary of the 3-D grid-based velocitymodeling procedure is discussed here.

In this grid-based velocity modeling, check-shot data fromeight wells and 15 interpreted horizons were used. All the 15interpreted horizons were used to create the 3-D grid toincorporate the structural information contained in the hori-zons. The PSDM interval velocity was sampled into the 3-Dgrid. Check-shot data from the offset wells is upscaled andsampled in the same 3-D grid. In the final step, the PSDMinterval velocity was calibrated with upscaled check-shot byapplying anisotropy factor derived from check-shot intervalvelocity and seismic interval velocity.

It is observed that check-shot-calibrated velocity is givingbetter match with the sonic velocity at all the well locations,which were used for calibration. The calibrated velocity cubeis validated at blind well location, and a good match isobserved with the sonic/check-shot velocity (see Fig. 7a).The calibrated 3-D PSDM velocity is shown in Fig. 7b.

3-D density calculation and calibration

3-D check-shot-calibrated velocity cube is converted to den-sity cube using Gardner’s equation (Fig. 8a). The Gardneret al. (1974) equation (Eq. 1) is given as

ρ ¼ aVb ð1Þ

where ρ is the density, V is the P-wave velocity, and a and b arethe empirical parameters.

The Gardner parameters for the study area are obtainedfrom the cross plot of sonic and density log. Density calculat-ed using Gardner’s equationwas extracted at well location andcompared with the density log. The density obtained from theseismic velocity was slightly lower than the well log density.To minimize the discrepancy between the observed log den-sity and calculated density, 3-D density cube is calibrated withthe well log density by applying the same technique used for

Fig. 7 (continued)

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velocity calibration. The calibrated density cube is validatedby exporting the density data at blind well locations. A goodmatch is found between the calibrated density and the logdensity (Fig. 8b). Overburden pressure is calculated using thecalibrated density cube. In the marine environments, overbur-den pressure σv at depth z is given as by Eq. 2.

σv zð Þ ¼ ρwgzw þ zw

zρ zð Þgdz ð2Þ

where ρw is the seawater density, zw is the water depth, ρ(z) isthe density at depth z below the surface, and g is theacceleration due to gravity.

Pore pressure prediction

The Eaton (1972) and Bowers (1995) methods were used forpore pressure prediction using 3-D PSDM interval velocity inthe study area. The Bowers method is based on the effectivestress approach and can be used to predict overpressure gen-erated by either undercompaction or fluid expansion mecha-nism (Bowers 1995). The Eaton method is based on thedetection of changes in porosity with depth and is derivedfrom Terzaghi (1948) equation (Eq. 3) based on soil mechan-ics (Eaton 1972).

Sv ¼ σv þ P f ð3Þ

Here, Sv is the total vertical stress, Pf is the pore fluidpressure, and σv is the vertical effective stress.

�Fig. 8 a 3-D density calculated from calibrated PSDM interval velocity.b Comparison of log density (RHOB) with seismic velocity-generateddensity before and after calibration with log density at blind well location.Seismic generated density is showing good match with the log densityafter calibration. Scale bar for density cube is in gram per cubiccentimeter

Fig. 9 a 3-D pore pressure prediction from calibrated PSDM intervalvelocity using Eaton exponent 3. b 3-D pore pressure prediction fromcalibrated PSDM interval velocity using Eaton exponent 6. Pore pressurepredicted using Eaton exponent 3 matches with repeated formation test(RFT) pressure data at shallow zone, whereas pore pressure predictionusing exponent 6 matches with the RFT pressure data in the deeper zone.

Hence, Eaton exponent 3 and exponent 6 can be used for pore pressureprediction at shallower and deeper zone, respectively. Red lines show thelocations of the wells for which RFT pressure data is available. The wellstaken as blind well for pore pressure validation are highlighted blue (wellA) and black (well B). The scale bar for both cubes (a, b) is in pounds pergallon

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Pore pressure prediction results obtained from bothmethods were compared with the RFT pressure data. TheEaton method is giving better pore pressure prediction, where-as the Bowers method did not give satisfactory results andunderpredicted the pore pressure. Therefore, pore pressureprediction using the Eaton method is discussed in this paper.

The Eaton method estimates pore pressure from the ratio ofacoustic travel time in normally compacted sediment to theobserved acoustic travel time (Hoesni 2004). The Eaton meth-od is given as in Eq. 4.

Pp ¼ Sv− Sv−Phð Þ V obs=V normð Þ Xð Þ ð4Þ

Here, Pp is the pore pressure, Ph is hydrostatic pore pres-sure, Sv is the total vertical stress, Vnorm is the normal velocity,Vobs is the observed velocity, and X is the Eaton Exponent(resistivity=1.2, velocity=3).

The Eaton method is an empirical method to estimate porepressures from seismic velocity, sonic, and resistivity logs.The Eaton method uses a regionally defined exponent (Eatonexponent) that can be varied to calibrate the trend and predict

the pore pressure generated by different mechanisms. In theareas where mechanism of overpressure generation isundercompaction, an Eaton exponent of 3.0 is typically usedfor pore pressure prediction.

Pore pressure cubes using Eaton exponent 3 and exponent6 are shown in Fig. 9a, b. This predicted pressure using theEaton exponents is extracted at two blind well locations (wellA, well B, and well C) as shown in Fig. 10a, b. The observeddiscrepancy between the RFT pressure and the predicted porepressure from the Eatonmethod has been used as an indicationof additional pressuring mechanisms besides disequilibriumcompaction.

Pore pressure was successfully predicted using an Eatonexponent of 3.0 in the shallower zone where the overpressureis believed to be generated by disequilibrium compaction. Inthe deeper part of the wells where overpressure is generated byfluid expansion, Eaton exponent 3 underpredicted the porepressure. However, a reasonable pore pressure prediction wasobtained by applying correction on the Eaton method (i.e.,using the higher Eaton exponent of 6), determined fromcalibration with RFT pressure data.

Fig. 9 (continued)

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Conclusions

Based on the results obtained from pore pressure prediction, itis concluded that well-conditioned PSDM interval velocity

can be used for predrill overpressure prediction using theEaton method in the study area. A refined interval velocitymodel can be obtained by calibration of PSDM interval ve-locity with check-shot velocity data and thus can be used for

Fig. 10 Example of predicted pore pressure using Eaton exponent 3 (redline) and exponent 6 (green line) at the blind wells, well A (a) and well B(b). The predicted pressure is compared with the RFT pressure data (blackdots). In both the wells, onset of overpressure is well predicted using

Eaton exponent 3. However, in the deeper zone, overpressure isunderpredicted. After applying the correction (i.e., using higher Eatonexponent), the Eaton method gives good prediction in the deeper zone

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overpressure prediction in the area of interest. Calibration ofdensity obtained from seismic interval velocity with the welllog density can also contribute to enhance the accuracy of porepressure prediction. The mismatch observed between the for-mation pressure and predicted pressure is attributed to thepresence of different mechanisms of overpressure.Anisotropic Kirchhoff PSDM interval velocity has increasedthe accuracy and reliability of the pore pressure prediction inthe study area.

Acknowledgments We wish to thank the Universiti TeknologiPETRONAS (UTP), PETRONAS Carigali, and Petrofac for providingthe data and permitting to publish these findings. We are thankful toFaizal Rahim and M. J. Hoesni from PETRONAS Carigali and Muham-mad Sajid from UTP for their valuable suggestions and discussions.Thanks are due to Geovani Christopher from the Halliburton Services,Kuala Lumpur, for providing software support. Special thanks are givento the Center of Seismic Imaging (CSI), Universiti TeknologiPETRONAS, for providing facilities to carry out this research work.

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