stratigraphic and lithologic interpretation of thin

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Stratigraphic and Lithologic Interpretation of Thin Reservoirsthrough an Integrated Approach: A Case Study

A. Bose, V. Singh, A.K.Tandon, B.S.Josyulu & Mahesh ChandraGEOPIC, ONGC, Dehradun

5th Conference & Exposition on Petroleum Geophysics, Hyderabad-2004, India PP 742-751

ABSTRACT : Conventional interpretation techniques are not found suitable to map thin clastic reservoirs with confidence due toinherent problem of seismic resolution. In order to define a more accurate reservoir model for improved reservoir understanding anddrilling of new wells, an advanced quantitative methodology integrating 3D post stack seismic data, impedance logs and geologicalknowledge was applied. The steps involved are well log analysis and their unitwise correlation, seismic wavelet estimation andwell to seismic calibration, horizon tracking, instantaneous and multi-dimensional attribute analysis for structural mapping,stratigraphic interpretation using window-based attributes and 3-D post stack stratigraphic inversion. After well to seismic tie andwell log correlation, the major stratigraphic markers were tracked in the 3-D seismic data volume, instantaneous and multi-dimensional attributes were generated for structural mapping. For stratigraphic interpretation, window-based amplitude attributeswere generated and analysed but they were not very helpful in deciphering the reservoir geometry. For obtaining layer by layerdetailed information of thin reservoirs; post stack stratigraphic inversion was carried out. This has maximized the verticalresolution and minimized the tuning effects. This paper demonstrates the effectiveness of this methodology through a case study.The study area falls in Cambay-Tarapur block of Cambay basin, India. The producing reservoirs in this area are from MioceneBasal sands. It has been observed that lateral facies variation of producing sands are very frequent which pose a major challenge indelineation and development of these reservoirs. This integrated approach has helped in delineating these reservoirs for theireffective characterization.

INTRODUCTION

Delineation and development of thin reservoirs withlimited areal extent have been a challenging task in the oil andgas industry. A sizeable amount of hydrocarbon is stillentrapped in such reservoirs and is unexplored. Stratigraphicinterpretation of 3-D seismic data is usually performed on amigrated volume having limited signal bandwidth. This band-limited nature of propagating seismic data fixes the practicallimit of seismic resolution and seismic record containsinformation only on that part of the spectrum of the stratifiedearth, which corresponds to the signal’s bandwidth. Whilecorrelating reflectors in migrated data volume, geophysicistsinterpret interface geometry, which depends upon thevariation of impedance contrasts, and thin layer interferences.Window-based 3-D seismic attributes are extensively beingused in the industry to predict subsurface properties (Taneret al., 1995, Chen and Sydney, 1997, Pramanik et al., 2003b,Srivastava et al., 2003). Most often, it has been observed thatseismic attributes derived from time, amplitude and frequencydo not provide adequate reservoir properties on a layer bylayer basis due to limited frequency bandwidth. Layer by layerinformation can be derived through from 3-D stratigraphicinversion of seismic data in terms of acoustic impedance. Thisinversion combines geophysical, geological and petrophysical

data through a robust inversion scheme to extract the morereliable stratigraphic information and reservoir properties (VanRiel, 2000, Vig et al., 2002, Pramanik et al., 2002, 2003a). Thispaper is an attempt to demonstrate a methodology forcombining well log information and 3D seismic data to definea more accurate reservoir model used for drilling of new welland improved reservoir understanding through a case study.The implication of this approach on delineation of thinreservoir has been discussed finally.

GEOLOGICAL BACKGROUND

The study area is located in the Cambay-Tarapurblock of Cambay Basin, India (Fig.1). It lies between Vatrakand Mahi River and is situated to the west of the Cambayfield. The N-S trending paleohighs with bounding faults ofthis field are considered to be genetically related to thebasement related paleohighs of Cambay and Gulf areas havingN-S orientation. These Anticlinal features have producedhydrocarbons from Miocene reservoir rocks in commercialquantity. Some oil indications from Eocene and Oligocenereservoirs of Kalol and Tarapur Formations were also observed.The generalized stratigraphy of the study area is shown inFig.2. Both Tarapur and Kalol Formations are inferred to havebeen deposited under alternate regressive and transgressive

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Stratigraphic and Lithologic Interpretation of Thin Reservoirs

Figure 1 Index Map of Cambay Basin showing Study Area.

Figure 2 : Generalized Stratigraphy of Study Area.

cycles indicating fluctuating brackish to shallow marineconditions. The marine transgression was most pronouncedand widespread during late Eocene period depositing TarapurFormation. The uppermost Babaguru section is considered tobe of fluvial to shallow marine origin. The availability ofcomparatively better reservoir facies corresponding toMiocene Basal Sands (MBS) and Oligocene sands atpaleohighs has been attributed to the better reworking of thesesands by tidal processes with subordinate wave action inshallow marine conditions. The Kalol Formation consists ofsilty shale with minor coal bands and silty claystone orsandstones. The sands encountered in Kalol Formation arelenticular and discrete in nature. The Tarapur Formationconsists of predominantly argillaceous facies composed ofclaystone/shale and minor siltstones streaks. The sequenceof Babaguru Formation comprises shale, claystone, siltstoneand sand. The sandstone is moderately hard to friable;dominantly medium to coarse grained poorly sorted with somefine to medium grained assemblages. It has been establishedthrough various studies that the essential elements ofpetroleum system, namely a source rock, reservoir rock, sealand overburden and the processes involved such as trapformation, generation, migration and accumulation alreadyexist in the study area. The occurrence of these essential

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elements and processes in time and space has allowed organicmatter of source rock to get converted into a petroleumaccumulation. The quantity, quality and thermal maturity ofthe organic matter determine petroleum source rocks potential.The potential source rocks in the study area are Tarapur, Kaloland Cambay shales. TOC ranges from 0.58 to 5.98% in Tarapur,0.55 to 62.8% in Kalol and 0.61 to 14.3 % in Cambay shales.The high value of TOC in Kalol is due to presence of coal(Chandra et al., 2001). The amount and type of organic matterand its level of thermal maturation indicate that Cambay shaleis the main source rock. Miocene Basal sands of BabaguruFormation are the main reservoir rocks, which are depositedin a fluctuating littoral to shallow marine environment. Theoverlying thick clay section on the top of Babaguru Formationacts as a seal for hydrocarbon entrapment. Strati-structuralnature of hydrocarbon entrapment in Miocene Basal sands(MBS) has made the systematic delineation and developmentof these clastic reservoirs a challenging task for theexplorationists.

DATA BASE

3D seismic data covering an area of 64 squarekilometers was acquired using dynamite as an energy source,keeping in view the precise mapping of Miocene Basal sandas one of the main objectives. A four-receiver line/eight shotline swath shooting geometry having a bin size 20mx40m wasadopted for the recording. This resulted in 32 fold seismicdata at a sampling interval of 2 ms and record length of 4 s.Utmost care was taken during data acquisition to achievemaximum signal to noise spectral bandwidth for higher lateraland vertical resolution. This was further improved throughgeometrical spreading and inelastic energy loss compensation,deconvolution and migration. A standard 3D processingsequence was applied to process this data volume with strictquality control of outputs at every processing stage. A singlewindow predictive deconvolution procedure was applied tothe prestack data using operator lengths (OL) of 160 ms,prediction distances (PD) of 2 ms and white noise of 10 percent.Close grid velocity analysis with 500 m x 500 m grid on prestacktime migrated gathers was carried out. Post stackdeconvolution was applied on the stack with an operatorlength of 200 ms and PD of 20 ms. The finally processed datavolume has broad-frequency bandwidth with dominantfrequency in the range of 35-40 Hz at the zone of interest (1.0to 2.0 s). This migrated 3D seismic data volume along withwireline logs from 13 wells (generally including Gamma ray,resistivity, SP, neutron, sonic and density) from the study


area, geological information and testing results of the wellswere used for interpretation.

WORKFLOW

The proposed workflow includes the understandingof petroleum system, well log analysis and their correlation,wavelet estimation and well to seismic calibration, structuralmapping and startigraphic interpretation using window-basedseismic attributes and seismic inversion. The essential elementsand processes of petroleum system in the study area wereanalyzed based on geological and geochemical data. Variouswell logs such as sonic, density, Gamma-ray and neutron logsavailable in the study area were simultaneously analyzed toderive an electrofacies interpreted in terms of lithofacies aftercalibration with five cored wells. Lithostratigraphic boundariesof different units of Babaguru, Tarapur, Kalol, and OlpadFormations were established in all the wells of the study area.Vertico-lateral facies distribution and lateral lithologicalvariations were also analyzed on the basis of well log data(Fig.3a). Finally, Miocene Basal sands were divided into foursubunits from top to bottom and subunitwise correlation wasmade for detailed analysis (Fig.3b). The thickness of individualsand subunit varies between 2 to 8m. The subunit-I is presentin wells A, B and C only whereas all other subunits are availablein all the drilled wells in the study area. Seismic to well logcalibration is the first step in integrating the seismic data withlog properties. It has been observed that misties of + 20ms arequite common in the study area and they present no simplepattern. The major cause for misties between synthetics andreal seismic data is severe variation of seismic wavelet. In thiscase Synthetics generated with a constant or minimum phasewavelet were unable to match with the complex seismic wavelet which changes both vertically and laterally. First, the waveletwas extracted from the seismic data and then 3D seismic datavolume was zero phased using this wavelet. Then a finalwavelet was extracted using multi-well and multi-traces. Afterextracting final seismic wavelet, synthetic seismogram isgenerated using sonic and density logs and VSP time depthcurve available in different wells of study area. Synthetic isthen tied to the seismic data, performing a constrained minorstretching and/ or squeezing to fit the major events. Thestretching/squeezing is primarily due to dispersion betweenseismic velocities and sonic velocities. This approach hasresulted in high quality match between synthetic and realseismic data at different well locations (Fig.4). After well toseismic tie at different locations, the seismic eventscorresponding to the tops of horizons namely Babaguru,

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Tarapur, EP-II, EP-III, EP-IV and Olpad tops were trackedthroughout the 3D seismic data volume. A display of zero


Figure 3b : Log Motifs of Miocene Basal Sands .

Figure 4 : Calibration between well log, synthetic and seismic dataat well D.

phased seismic section passing through wells A, B, C & D isshown in Fig. 5. For delineation of fault pattern at differentlevels more precisely, a number of seismic attribute volumessuch as inst. amplitude, inst. frequency, inst. Phase throughcomplex trace analysis, multi-dimensional attributes (dip, dip-azimuth and coherency volumes) were generated from time

Figure 3a : Log Correlation Profile Through Wells - A,B,C,D & E.

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Figure 5 : RC Line passing through wells - A,B,C,D&E

component of 3D seismic data volume. The time structuremaps were prepared for different correlated horizons. Window-based seismic attributes corresponding to Miocene Basalsands were generated for stratigraphic interpretation. To obtainthe layer wise information of producing Miocene Basalreservoirs, model based stratigraphic inversion was carriedout. The steps involved are spectral analysis, statisticalanalysis, wavelet estimation and calibration of seismic data towell log data, initial 3D-impedance model, inversion schemeand validation of results obtained after inversion for qualitycontrol. This inversion technique has modeled the earthsubsurface as layers or blocks in terms of acoustic impedanceand time and generated an impedance volume for furtheranalysis.

RESULTS AND DISCUSSION

The comparison of synthetic and real seismic at welllocations offer physical insight into how well the seismic datahave been processed and how well the forward-modeled welllogs depict actual in situ geology. The time slices generatedfrom instantaneous and multi-dimensional seismic attributevolumes have been very helpful in deciphering the fault patternthrough which even subtle faults became discernible (Fig.6).The fault pattern obtained by these attributes reveals that thearea has been subjected to polyphase deformation and theiralignment is in conformity with the major tectonic trends ofCambay basin. The main NNE-SSW configuration oflongitudinal faults delineated mainly in the central parts of the3D area represents the older faults. These fault trends appearto have contributed greatly in the formation of two NNW-SSEstructural features. The E-W aligned fault patterns were

reactivated during different geological times and haveobliterated the original trends of older faults. As a result, ofpolyphase episodic deformation systems, many of the faultscut across each other or take sudden swings. These NNW-SSE and E-W trending fault patterns compartmentalize thestudy area in to number of fault blocks, which appear to beimportant from hydrocarbon exploration and developmentpoint of view. The structure contour map prepared using 3D-velocity grid and VSP data at the top of Miocene Basal sandsis shown in Fig.7. There are two major well-defined NNW-SSEtrending horst features bounded by well-defined faults with alow in between. A similar and comparatively sharper trend isseen at basement level also. There exist a major low in thenorth constituting part of the main Tarapur depression. BothNNW-SSE trending horst features terminate in this depression.The window- based seismic attributes generated from 3Dseismic data volume were not very useful for quantitativestratigraphic interpretation (Fig.8). It has been observed atplaces that this attribute map does not fully explain thepresence of sand, which have been encountered in alreadydrilled wells. In order to delineate these sands effectively,post stack seismic inversion was carried out. The Cross-plotanalysis of well log data carried out prior to post stack seismicinversion has provided a solid base to understand the relationbetween seismic parameters, acoustic impedance, velocity anddensity. This analysis has been very helpful for prediction oflithology in distinguishing reservoir and non-reservoir shalyfacies and also in establishing the relation between thereservoir property and each of the acoustic properties (Fig.9).A display of impedance section corresponding to the verticalseismic section shown in Fig. (5) is extracted from the invertedacoustic impedance volume and is shown in Fig.10. Thewindow-based time slices (Fig.11) are generated from acousticimpedance volume for different subunits of Miocene Basalsands considering their average thickness encountered at wellpoints. These impedance slices have clearly brought out theindividual reservoir geometry, their areal extent, revealed thenew entry of the sands and enlargement of the sand lobestowards the south-east. These south-east trending sand lobesare mostly channel deposits with tidal influence from south-east. Further, these impedance slices of different MBS unitsalso demarcate multi-channel entry of reservoir sands in thestudy area. The sand isolith map (Fig.12) prepared from theactual sand thickness encountered at drilled wells matcheswell from the interpreted sand distribution through impedanceslices.

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Figure 6 : Instantaneous and multi dimentional attribute slices at 1392 ms.

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Figure 7 : Depth Map at the top of Miocene Basal Sands.

Figure 8 : Amplitude Attribute Map of Miocene Basal Sands.

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Figure 10: Impedance Section of RC line passing through Wells -A,B,C,D&E.

Figure 9 : Crossplots between Impedance vs. Sonic Impedance vs. Density and Impedance vs. Gamma Log.

CONCLUSION

The integrated approach of interpretation adoptedin this case study has resulted in precise mapping of reservoirsand geometry. The instantaneous and multi-dimensionalseismic attributes were very useful in deciphering the faultpatterns and structural trend present in the study area.Acoustic impedance has provided a superior basis for detailedreservoir characterization compared to reflection amplitudesand amplitude based attributes. Higher vertical resolution andaccurate layer by layer lateral extrapolations of acoustic

impedance has proved an ideal parameter to improve thestratigraphic interpretation, sedimentary architecture, lithologyprediction and to refine the drilling plan of development andnew exploratory wells.

ACKNOWLEDGEMENTS

Authors are grateful to Oil and natural GasCorporation limited, India for providing the necessaryinformation and infrastructural facilities to carryout this work.Authors acknowledge their sincere thanks to Dr.C.H.Mehta,GGM (Prog.) & Head, GEOPIC for his valuable guidance andto Director (Exploration), ONGC for according permission topublish this work.

REFERENCES

Chandra, K., D.S.N. Raju, A. Bhandari and C.S.Mishra, 2001,Petroleum systems in the Indian sedimentary basins:Stratigraphic and geochemical perspectives, Bulletin ofthe ONGC, V-38, No.1,1-45.

Chen, Q. and Sidney, S., 1997, Seismic attribute technology forreservoir forecasting and monitoring, The leading edge,May issue, 445-456.

Pramanik, A.G., Srivastava, A.K., V.Singh and Katiyar Rakesh,2003a, Stratigraphic interpretation using post stackinversion: case histories from Indian Basins, Paper No. P-52, Expanded abstract, 65th EAGE Conference held inJune 2-6, at Stavenger, Norway.

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Figure 11 : Sand distribution and corresponding Impedance of different units of Miocene Basal Sands


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Pramanik, A.G., V.Singh and A.K.Srivastava, 2003b, SeismicAttributes and Their Role in Reservoir Characterization,Proceedings of PETROTECH-2003 held in January 2003at New Delhi.

Pramanik, A.G., V.Singh, Srivastava, A.K. and Katiyar Rakesh, 2002,Stratigraphic Inversion for enhancing vertical resolution,GEOHORIZONS, 7(2), 8-18.

Srivastava,A.K., V.Singh, B.G.Samanta, and G.Sen,2003,Utilization of Seismic Attributes for Reservoir Mapping:A Case Study from Cambay Basin, India, CSEGRecorder,V-28,No.-8, 46-50.

Taner, M.T., 1995, Schuelke, J.S., Doherty, R.O. and BaysaL, E.,1995, Seismic attributes revisited, expanded abstract,Society of expl. Geophys., 1104-1106.

Van Riel, P., 2000, The past, present and future of quantitativereservoir characterization, The leading edge, V-19,No.8,878-881.

Vig, R., Singh,V., Kharoo,H.L.., Tiwari, D.N., Verma, R.P., Chandra,M., and Sen, G., 2002, Post stack seismic inversion fordelineating thin reservoirs: A case study, Proceedings of4th conference & exposition in Petroleum Geophysics(Mumbai-2002) held during January 7-9, 287-291.

Figure 12 : Sand Isolith Map of Miocene Basal Sands


stratigraphic and lithologic interpretation of thin

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