Geophysical Technology Integration in Hydrocarbon ... · and innovations in seismic related technologies are proving to be more important in the develop-ment of oil and gas fields

1 GEOHORIZONS Vol .6 No. 2April 2001

Geophysical Technology Integration in Hydrocarbon Explorationand Production: An Overview

•A.G.Pramanik •P.K.Painuly • V Singh •Rakesh KatiyarGeodata Processing and Interpretation Centre

Oil and Natural Gas Corporation Limited, Dehradun-148195, U.A., India.

Summary:

During 90’s gpophysical technologies have played increasing role in economic success acrossthe E & P businesses. As fields become more difficult to locate and evaluate, the new developmentsand innovations in seismic related technologies are proving to be more important in the develop-ment of oil and gas fields than any other technology areas. These trends as well as growth of newcapabilities indicate that the geophysics can be more important in coming years if geophysicaltechniques interven with integration of various domain with special focus on subsurface imaging,reservoir prediction, description, characterization and management. This will lead to improvedefficiency, cost effectiveness and higher productivity. With true integration of data, disciplines andknowledge, the potential of geophysical technology add even more value tomorrow than it doestoday seems to be unquestionable. It is up to the geophysical community tddeliver and effectivelydemonstrate the quantitative value of these techniques in seismically driven reservoir risk manage-ment.

Introduction:

The sustainable economic growth of acountry depends progressively on higher levelsofeneigy consumption. Petroleum is the mostcritical energy source and a major determinantof global development and prosperity. Rapidurbanisation and industrialisation has led tomultifold increase of petroleum consumption anddemand of petroleum products continue to growwith no sign of abatement The task of findinghydrocarbon reserves is becoming more and morechallenging day by day, a»the easy to find oil hasalready been exploited. Further, exploration isin high risk areas which are logistically difficultand geologically complex. A number of practi-cal problems such as detection and resolution ofthinly laminated sand-shale sequences, distribu-tion of faults, fault type, magnitude of throw andcharacteristics, discrimination between sealingand nonsealing faults, detection and delineationof fractures zones , macro and microscopic het-erogeneity, subsalt and subbasalt imaging, im-aging of the subsurface in complex geologicalset-ups (deep water, gas chimney, volcano, karst), fluid and permeability prediction are some of

the challenges before us. These problems fallinto two major categories (1) Structural problemsin nature and (2) reservoir related issues.

To address these challenges, the horizonsof geophysical techniques integrated withpetrophysical, geological, reservoir and comput-ing technologies will have to be stretched to newboundaries and new technologies will have tobe adopted to make technological breakthroughspossible. This will require going beyond the con-ventional methods with their intrinsic resolutionand accuracy limitations. Significant advancesin seismic related technologies have been madewhich include effective energy sources, highlysensitive receivers, high resolution seismic re-cording systems for onland, offshore and bore-hole data acquisition, highspeed high memoryprocessing computers, high density disk storage,powerful seismic software’s for processing, in-terpretation, reservoir characterisation and 3Dvisualisations . Since the inception of commonmidpoint shooting in 1956, step by step advance-ments of seismic technology are summarised inTable -I (AAPG Explorer, 2000).The revolutionin the computing has brought a major shift from


mainframe computing to parallel computing andfurther to internet -enable computing environ-ment. The advantages of massively parallelprocessors(MPP) computing systems, highmemory, disk and on-line tape storage (of theorder of Terabyte) and high memory requirementof seismic data processing such as 3D AVO,DM0,3D prestack depth migration, full wave-form seismic inversion and time lapse 3Dseismics are being efficiently utilised in user-friendly interactive environment by the industlytoday. These advances have spurred significantimprovement in defining, predicting,characterising and monitoring the hydrocarbonreservoirs through integration of data, scales,resolutions and cross-disciplinary knowledge.Benchmarking and survey data of recent yearsindicate that new developments and innovationsin seismic related technologies have had higher

impact on E & P activities and indicate that over-all, geophysics is moving slowly much closer toreality from interpreting geology to illuminatinggeology to quantifying geology. An overview ofthese state -of-the-art technologies and their in-tegration have been presented in this paper.

Advances in Data Acquisition Technol-ogy:

Acquisition of seismic data with highestfidelity is an important aspect of hydrocarbon ex-ploration and exploitation. The significant ad-vances in computers, instrumentation and seis-mic acquisition technology have facilitated dataacauisition from single component 2D to threecomponent 3D onland and from single streamerto multi-streamer 2D and 3D, single component2D to multicomponent OBC surveys in offshoreareas (Fig. 1) ( Singh and Sen, 1998, Denny,2000). The increased number of recording chan-nels, capability of automatic QC-process to limitnoise and other intrusions beyond user- defmedlimit, telepresence module of the recording sys-tems, permanent placement of ocean-bottom re-ceivers with remote operating vehicles and ad-vanced Global Positioning Systems (GPS) fornavigation have greatly improved the operatingefficiencies and accuracy of the surveys.

Today, Global positioning system (GPS)is essentially the global navigation and position-ing standard throughout the world and is widelyused throughout the mineral and petroleum ex-ploration. From midnight of May 1,2000, USAhas stopped the international degrading of theGPS signals by deactivating the selective avail-ability (SA) feature. This has further improvedthe GPS positioning accuracy in public domain.Another major advance in marine seismic posi-tioning has been the advent of least squares net-work adjustment solutions in integrated naviga-tion systems. This mathematical approach hasallowed real time integration of the array of sat-ellite, laser acoustic and magnetic sensor mea-surements used to position multiple streamer/multiple source spreads. Schiumberger has de-veloped a new type of streamer positioning andsteering control system for offshore data acqui-sition that allows lateral steering of the towed


hydrophone streamers. This system includeonline steering device, built-in acoustic rangingsystem and a new integrated navigation system.Lateral steering system can steer cables upto 3degree laterally from natural streamer angle andsteamer can be reliably positioned within 2-3maccuracy ( Fisher, 2000). Controlledpositioningofstreamerswill ensure consistentcoverage and offset distribution. This will reduceerrors in processing and advanced binning tech-niques leading to more reliable reservoirmodel.Reduced turn - around times of operations havesignificantly reduced operating costs and pro-vided more accurate project informations in realtime.

Introduction of 24-bit Sigma Delta Tech-nology is an innovative step and a quantum jumpforward to improve the dynamic range of the seis-mic recording systems. Sigma Delta technologybased recording systems preserve the basic sig-nal characteristics (amplitude, frequency andphase) more effectively while signal passesthrough the recording systems. Sigma deltamodulation based A/D conversion first digitizesthe change in the signal from sample to samplethrough Delta modulator and then integrate it bySigma modulator (i.e.. Integrator). To improvethe effective dynamic range ( i.e., S/N ratio byreducing noise floor) and achieve higher resolu-tion, Sigma delta converter employs a single bittype ADC function at an over sampling rate on

Fig 2 a. Comparision between conventional andadvanced seismic acquisition with DGF process

Source: Me. Banet, 2000

Fig 2b: Comparison of array(24 sensor) and singlesensor seismic data

Source: Me. Banet, 2000

Fig 1. Schematic Diagram of Land and Marine Acquisition techniques


Fig 3: Schematic diagram of advanced bore hole seismology

original analog signal rather than a multi bit ADCfunction. Then this single bit signal is trans-formed to a 24 bit data stream at lower ratethrough digital filtering and decimation tech-niques. Digital filters provide high quality filterresponse with steady phase over a wide band offrequencies. This was not possible with analogdomain filters in IFP based systems, though de-signed with utmost care and judicious selectionof components. Thus, the improved dynamicrange from sigma delta technology has resulteddue to elimination of many circuit like filters,IFP and adoption of a new approach for A to Dconversion.

Recently in the month of March 2000,Schiumberger Oilfield Services has launched arevolutionary new seismic data acquisition and

processing method “Q” in terms of efficiency andwavefield fidelity for land. Q - Land enables30,000 channels of alias-free data to be acquiredin real time at a 2.0 m-sec. sampling interval (MoBaipet, 2000). This system also consists soft-ware to enable pseudo real time pre-processingof the many single sensor signals and flexibledigital group forming of individual data chan-nels as an integral part. A comparison of analoggroup forming process of conventional acquisi-tion is shown over the digital group forming pro-cess of novel acquisition in Fig. 2a. Higher fre-quencies are generally lost within a conventionalarray as small perturbations ( such as statics,elevation differences and others) have the effectof smearing the received signal. These perturba-tions can be corrected prior to group forming withthe DGF process, thus giving broad band data.


The resolution of the processed image can bevaried after acquisition to improve S/N ratio andoptimise resolution as required. Comparison oftwo stacked sections generated from 3 singlesensors and conventional array of 24 sensors re-corded data are shown in Fig. 2b. Stack sectionof 3 single sensors shows improved data qualityas diffraction event marked in the section isclearly resolved. This diffraction event is not re-solved in case of 24 sensors array data wherehigh frequencies are lost due to averaging.Schiumberger also launched an integrated seis-mic data acquisition system with calibrated singlesensors, positioning and sources for marine en

Fig 4a. Schematic Diagram of Sonic Reflection imagingSource: Esmersoy et al, 1998

Fig 4b: Horizontal well located in Oil Gas field reservoirimmediately beneath the cap-rock

Source: Esmersoy et al, 1998

Fig 4c: Raw record of Sonic reflection imagingSource: Esmersoy et al, 1998

Fig 4d: Migrated image of cap rock from P-wave data


vironment. Q-Marine exploits the advances inelectronics and data communication networks toallow the recording of more than 4000 individualhydrophones on single streamer with a maximumcapacity of 20 streamers and a total of 80,000channels. Q-Marine also incorporates sophisti-cated signal processing of the single sensor dataincluding intelligent, dynamic group formingwith correlation of perturbations ( swell noise,sensor sensitivity etc., ) in the towed streamerseismic data. Q-Marine ensures 4D repeatabil-ity, delivers qualified high resolution , high fi-delity towed – streamer seismic data, ready fortime lapse monitoring (First Break, 2000 a). Theimproved frequency content and both temporaland spatial resolution from these new techniqueslead to improved seismic images for complexgeological areas. Hardware constraints of acqui-sition are decoupled from imaging processes.This allows data processor or interpreter toanalyse the data to their best advantage.

Although, the resolution of 3D-3C/4Cseismic is crucial, the fundamental bandwidthand resolution limitations of these techniques canbe overcome only by borehole seismics. Bylaunching Q-Borcholc system at the SEG meet-ing held in Calgary, Canada during month ofAugust, 2000, Schiumberger has completed Q-system portfolio which started with Q-Land earlyin year 2000. This Q – Borehole system operateseither in standalone mode or simultaneously withQ-land and Q-marine, reduces operation timemore than half through faster anchoring anddisanchoring during vertical seismicprofiles(VSP) while maintaining the quality ofthe data. Schiumberger’s Q - Borehole can com-bine from one to twenty sensor shuttles anywherefrom 2.5m to 20m, with no limitation on num-ber of shuttles connected or length to use withinthe soecified ranee. An interconnecting cableuses regular multi-core cable giving absoluteflexibility in the field for choosing optimum in-ter-sensor spacing to eliminate spatial aliasing.Signal fidelity is achieved through smaller sen-sor package, with acoustic isolation housing threeaxis gpophones to keep tool resonance outsidethe useful frequency of seismic signal and toachieve good coupling in all hole conditions (First Break, 2000b). Further, the development of


80 levels three component (3 C) tflamped bore-hole seismic receiver array with geophone podspacing either 25 or 50feet, fiberoptic 25Mbit/sec seismic data transmission, clamped boreholeaxial vibrator, and onsite data processing havebeen very much useful in delivering high resolu-tion subsurface seismic images around the bore-hole in the quickest possible time (Paulsson,2000). A 1arge number of crosswell surveys withwell spacing exceeding 2.0km. and at depth ofmore than 6.0km have been carried out success-fully after these advances in borehole seismol-ogy ( Fig-3). Earlier, crosswell technique waslimited only upto 0.5km. interwell distance anddepth upto 3.km only due to lack of high energysources and multichannel clamped receivers (Lazaratos et al., 1993, Lee et al., 1995a, b). Theresults of recent crosswell surveys have providedhigh resolution images with improved accuracyand enriched the content model parameters suchas velocity, attenuation, anisotropy and layer ge-ometries (Sheline, 1998).

Recently, Sonic Reflection Imaging hasbeen developed which utilizes source-receivergeometry similar to sonic logging as shown inFig. 4a (Esmersoy et aL, 1998). A schematic dia-gram of a horizontal well located in the oil-filledreservoir immediately beneath caprock is shownin Fig.4b. Farther down in the reservoir, the poresare water filled. Drilling of a horizontal well at6m rather than 3m beneath top of reservoir cansignificantly reduce the oil production and a goodamount of oil will be left undrained in the reser-voir. As a result of continued production fromthe reservoir, the oil water contact will moveslowly toward the horizontal well. Once waterbreak through occurs at the well, it becomes vir-tually impossible to effectively produce the oilfrom the interval between well and caprock. Themain issue to resolve with the Sonic ReflectionImaging technology is the distance between welland the reservoir seal boundary. Unlike the log-ging, which uses the compressional and shearhead waves propagating on the fluid /formationinterface, sonic reflection imaging uses signalsreflected from structures outside the well. Hori-zontal wells drilled nearly parallel to bed bound-aries and fluid contacts provide the mostfavourable geometry for imaging these targets

using reflected sonic waves. A single shot gatherrecorded in a horizontal well is shown in Fig. 4cwith marked reflected signal in red. The migratedimage of the caprock at a range of 3 to 4m fromthe well through sonic reflection imaging isshown in Fig. 4d which clearly demonstrate thesuccess of this technology. The application ofthis technology to image caprock boundary withhigh resolution and high frequency up to therange between 3 of10m from the horizontal well trajectory has beensuccessfully demonstrated in many wells. Thisimaging has been very helpful in die placementof another horizontal side track closer to caprockwith considerable precision inside the reservoir.

Advances in Processing and Imaging:Developments in computing hardware

and software have allowed a number of theoreti-cal concepts to become practical. In addition topredictive deconvolution, theoretical conceptssuch as Fourier and Radon transforms, Eigenimaging , Kirchoff wave field continuation,acoustic wave equation solutions and large ma-trix solutions have all become practical. In re-cent years, tremendous advancement in computercapabilities in terms of ease of programming (object oriented), expanded storage ( cheaper,larger, faster and more reliable disk arrays), com-putational speeds. ( gigaflops on a desktop) andconvenient and fast colour monitors and plottershave been witnessed. A very big hall was requireda couple of decades ago to house a seismic pro-cessing computers; equivalent processing cannow be done on a laptop. Earlier, for a I millionoutput trace survey, a full 3D prestack depth mi-gration would have taken 10 to 15 years runtimeson mainframe conventional computers whereastoday, with parallel supercomputers and softwareadvances these runtimes have reduced to weeks.An illustration of runtimes for depth migrationprocessing at the interval of 5 years w.e.f. 1990given in Table-2 shows how this technology caneasily be applied today in a matter of hours us-ing an inexpensive desktop workstation. As aresult, number ofcomputationally difficult pro-cedures such as prestack depth migration, elas-tic imaging, generalised inversion etc., are be-coming more and more practical which are veryhelpful to the interpreters to better visualise and


understand the reservoir characteristics. Further,with these revolutions in computing and hard-ware, artificial intelligence applications havealso started playing a major role in achieving theobjectives of hydrocarbon exploration and pro-duction through better reservoir characterisation.

Multicomponent Technology:

The onland and offshore multicomponentseismology has been accepted as the state-of-the-art-technology. This has been made possible bya measure success in converted shear wave im-aging, the realization that P-waves are partly con-verted into shear waves at interface ( Singh andShamia, 1998). Three component seismic record-

ing captures the complete seismic wave fieldand has enabled geophysicists to gain more in-formation about the rock and fluid properties ofGas Filled Channel

Fig 5a P-P Wave amplitude map(Blackfoot field)Source: Margrave et al, 1998

the reservoir than using vertical receivers only.The combination of P- and S-wave data can yieldinformation about the fluids in the pore spacesand improve the potential for identifying the pros-pect lithology. The various advantages of multi-component seismic recording over P-wave in-clude higher vertical and horizontal resolution ,direct detection of hydrocarbons, lithologydescriminations and illumination of areas whereP-waves are blurred ( Pramanik et al„ 1999). Ithas been established that multi-component seis-mic data provides higher vertical and lateral reso-lution with the same frequency content in thecomparable P-P and P-S seismic data. The am-plitude maps of P-P and P-S waves extractedfrom 3C-3D seismic data volume of Blackfootfield. Alberta, Canada are shown in Fig.5a and b(Margrave et al., 1998). The channel sand runsfrom south to north along the western half of thesurvey and denoted approximately by the arrows.The black dots represent the producing wells. Acommon exploration technique is to pursue P-Pamplitude bright spots (large anomalous nega-tive amplitudes) of reservoir channel filled sandsbut there are some false anomalies also in P-Pwave amplitude map, whereas P-S wave ampli-tude map gives a much better suggestion of thechannel trends through the brightest amplitudes(large anomalous positive amplitudes). Theseamplitudes are displaced about 100-200m west-ward from the producing well trend. EstimationGas Filled channel

Fig 5b P-S Wave amplitude map(Blackfoot field)Source: Margrave et al, 1998


Gas filled Channel

Fig 6a Vp/Vs ratio map(Blackfoot field)Source: Margrave et al, 1998

Fig 7a: P-P wave 2-D stack section(Gulf of Mexico)

Source: Gaiser and Jones, 1998

of Poisson’s ratio being recognised as key indi-cator for detection of hydrocarbons in elastic res-ervoirs and is being done with greater accuracyand reliability by using both P & S wavereflectivity. Figs.(6a,b) showthatthe lowering of(V /V)ratio and fractional percentage of shale areindicative of hydrocarbon bearing sands(Maigrave et al., 1998).

There are several instances in which con-ventional P-wave survey do not adequately im-age a reservoir or describe its properties. Pres-ence of gas, even in small amount disrupts P-wave transmission and obscures underlying tar-gets from compressional surface seismic view.When gas is shallow it can cloud the entire sub-surface. Some of the reservoirs do not have suf-ficient impedance contrast to the overburden and

Gas filled Channel

Fig 6b Fractional percentage of Shale Map(Blackfootfield)

Source: Margrave et al, 1998

Fig 7b: P-S wave 2-D stack section(Gulf of Mexico)

Source: Gaiser and Jones, 1998

do not reflect P-waves strongly enough to pro-duce and interpretable image. In the areas, whereoverburden itself is a high impedance materialsuch as salt or hard volcanic rock, imaging theunderlying reservoir is difficult because so littleP-wave energy returns to surface after transmis-sion twice- down then up-through high imped-ance rocks. The ability of PS-wave to imagethrough gas chimneys is shown in Figs. 7(a,b)from the 4-component OBC data of NorthSea.(Gaiser and Jones,1998). The reflection fromthe mterfaces within and below a gas filled chan-nel are extremely poor on P-wave stack section.On the other hand S-wave section delineates thechannel base , interfaces below the channel andeven sediments within the channel. Another clas-sic example of low impedance reservoir situated


Fig 8a: P-P wave stack section(Alba field of North Sea)Source: Caldwell et al, 1998

in Alba field of North Sea (Figs. 8a, b, Caldwellet al„ 1999). This reservoir is a poorly consoli-dated Eocene turbidite sand channel ( about9.0km long, 1.5 to 3.0 km wide and thicknessupto 100m ) and was completely invisible on con-ventional P-wave data. This field was discoveredunexpectedly, while drilling to a deeper target.On the analysis of compressional and shear soniclogs, it was found that there is no P-wave im-pedance contrast but very high shear wave im-pedance contrast at the top of reservoir. This be-came the basis for conducting multicomponentsurvey over Alba field of North Sea. The pro-cessed converted wave section shows clear top,base, lateral extension and even compart-mentalisation of the channel sand.

Most of the sedimentary rocks displayvelocity anisotropy to some degree or order dueto vertical oriented fractures and or unequal hori

Fig 9a: AVO Product(intercept * gradient) using -2Term NMO corrected gather(conventional)

Source: Rass, 1997

Fig 10a: Fluid factor(intercept + gradient) section using2-Term NMO corrected gather(Conventional)

Source: Rass, 1997

Fig 8b: P-S wave stack section(Alba field of North Sea)Source: Caldwell et al, 1998

zontal stresses. Case studies have shown that thepresence of aligned fractures cause azimuthalanisotropy. The successful adoption of multi-component seismology has given a new dimen-sion for estimation of anisotropy, which is re-lated with the density of fractures and their ori-entation( Li et al., 1997). The detection of frac-tures is highly useful in the placement of hori-zontal wells and for reservoir characterisation.Thus, multicomponent technology is leading to-wards the fulfilment of ultimate aim of seismicexploration in terms of improving reservoir per-formance and enhanced hydrocarbon recovery.It has emerged as “A True Production Enhance-ment Technology”. Upto 1998, most of the mul-ticomponent operations were usually ever was130 squire kilometers acquired by M/SSchiumberger Geco-PrakIa in the North sea. See-ing the potential of this technology, very recently,world’s largest multicomponent survey covering

Fig 9b: AVO Product(intercept * gradient) using -3Term NMO corrected gather (non hyperbolic)

Source: Rass, 1997

Fig 10b: Fluid factor(intercept + gradient) section using3-Term NMO corrected gather(non hyperbolic)

Source: Rass, 1997


Fig 11a. Amplitude map from conventional 3-D volumeSource: TLE, Aug 1999

Fig 12a: Amplitude map from conventional 3-D volumeSource: AAPG Explorer, 1999

Fig 12c: Amplitude map from 3-D AVO large anglestackSource: AAPG Explorer, 1999

1000 square kilometers was conducted in theWest Cameron area of Gulf of Mexico (Stefanic,2000). A renowned geoscientist Dr. BobHardage, , Bureau of economic geology. Univer-sity of Texas at Austin, USA has expressed hisviews that Miilticomponcnt seismology is head-ing towards a new technical revolution in theseismic industry like earlier revolutions fromrefraction to reflection imaging, analog to digi-tal recordings, invention of CDP technique andin 1980’s from 2D to 3D imaging seen in thepast.

2D and 3D AVO:

Amplitude variation with offset (AVO)

Fig 11b. Amplitude map from 3-D AVOSource: TLE, Aug 1999

Fig 12b: Amplitude map from 3-D AVO small anglestackSource: AAPG Explorer, 1999

Fig 13: Flow chart for Velocity Model Building

is a tool being used extensively for hydrocarbonexploration and exploitation. AVO attributes (in-tercept,, gradient, fluid factor and their combi-nations) interpretation in 2D and 3D sense forclastic gaseous reservoirs have been used suc


Fig 14 a: 3-D post-stack time migrationSource: Fagin, 1998

cessfully and have proved to be more reliablefor quantizing risk specially in deep water areas(Hilterman, 1998, Pramanik et al., 2000). Ad-vantages of advanced computing facilities on 2DAVO analysis on a Gulf of Mexico seismic datacan be clearly seen on AVO product and Fluidfactor attributes shown in Figs. (9a, b) andFigs.(10a, b) respectively. Two—term (conven-tional) NMO corrected gather and three-term(nonhyperbolic) NMO corrected gathers havebeen utilized for extracting basic 2D AVO at-tributes intercept and gradient to generate AVOproduct and fluid factor attributes (Ross, 1997).The amplitude maps extracted from the conven-tional 3-D data volume of Gulf of Mexico donot provide adequate stratigraphic details becauseof averaging of amplitudes across all offsets,where as 3D AVO can provide several limitedoffset volumes which may be rich in stratigraphicdetails (Figs lla,b. The leading edge, 1999). Thevariation of amplitude strength for a known gas-eous reservoir of Gulf of Mexico in 3D AVOsmall angle and large angle stack volumes canbe seen clearly which is not possible in case ofconventional 3D data volume(Figs. 12a,b and c,AAPG Explorer, 1999). Thus, 3D AVO providesclear stratigraphic definition, improved reservoirdescription, better evaluation of prospect and itseconomics, prospect risk assessment, optimiseddrilling location/ platform placement and moreefficient field development. The application ofAVO analysis in the characterisation of carbon-ate reservoirs has great potential but faces chal-lenges. With the better understanding of the re-lationships between carbonate rock properties,wave propagation phenomena and AVO ( Kumaret al.,1996, Carcione et al„ 1998), it is expected

Fig 14 b: 3-D pre-stack depth migrationSource: Fagin, 1998

to derive more meaningful inforination frotoAVO and utilise its full potential for both clasticand carbonate reservoirs.

Depth Imaging:

Depth imaging is changing the face ofseismic technology. Interpretation of depth mi-grated data has become increasingly commonowing to advances in both post and prestackdepth processing. Depth domain processing canprovide better subsurface imaging than the con-ventional time domain if an accurate velocitymodel is prepared with understanding of geologi-cal features. Velocity modelling is typically it-erative and requires many runs ofcomputationally intensive prestack depth migra-tion. A schematic diagram of accurate velocitymodel building is given in Fig. 13 ( Jones et al.,1998). Continuous improvement in the depthimaging and velocity modelling through inten-sive computation has improved subsurface im-ages many folds. A comparison of a 3D post stacktime migrated section with a 3D prestack depthmigrated section from onshore Poland exhibit-ing fault shadow image distortions is shown inFigs. 14a and b ( Fagin, 1998). The time imagedisplays little signal in the platform section tothe left of the main bonding fault of the graben.In contrast, the depth image displays the struc-ture clearly and offers superior imaging of thefault plane as well. But the current state-of-the-art for creation of accurate subsurface images indepth using geophysical measurements made intime is still far away from the ideal. New meth-ods of dip moveout (DM0), 3D prestack depthmigration with anisotropy effects and elastic


Fig 15 b: Isotropic & Anisotropic PSDM VerticalSection

Source: Hawkins et al, 2000

waves are being developed. Accurate velocitymodels using a combmation of surface andcrosshole tomography, and added bythree com-ponent measurements are also being investigated.Given the need to tackle depth imaging and res-ervoir characterisation problems in tandem, pro-cessing methods with preserved amplitude andother attribute information are gaining impor-tance. Three dimensional velocity modelling isexpected to play a bigger role in designing seis-mic surveys, validating depth imaging and res-ervoir characterisation. To accomplish this, elas-tic version of 3-D models will have to be simu-lated after including subsurface properties includ-ing elastic, anisotropy and attenuation param-eters.

Generally, the propagating seismic wavesis treated under four assumptions:(l) that themedium is isotropic(2) that the medium is ho-mogeneous(3) that there is one to one relation-ship between stress and strain and (4) that stressesare linearly related to strains (equivalently, that

Fig 15 a: Seismic section with anisotropy parameter profile overlay


strains are linearly related to stresses). Real me-dia generally violate at least some and often allthese assumptions. A valid description of wavepropagation in real media thus, depends on thequalitative and quantitative description of therelavent inhomogeneity, anisotropy andnonlinearity (Amaud et al-,1999). In typical sub-surface formations, velocity changes with bothspatial position and propagation direction. Thismakes the medium heterogeneous and anisotro-pic. Anisotropy in sedimentary sequences iscaused either due to thin bedding of isotropiclayers on a scale small compared to wavelength,preferred orientation of isotropic mineral grains/the shape of

isotropic materials, vertical / dipping fractures,microcracks or by certain combination of thesefactors (Singh et al., 1997, Singh, 1998). As aresult, subsurface formations may possess sev-eral anisotropic symmetries, each with differentcharacter of wave propagation. Seismic signa-tures for the most general symmetry depend on21 independent stiffness coefficients as comparedto just 2 velocities in isotropic media. Estimat-ing these 21 coefficients is a problem of greatcomplexity and that can not be solved without acomprehensive set of measurements usually un-available in practice. The simplest and most com-mon anisotropic model is transverse isotropy withvertical axis ofsymmetiy(VTI media). VTI me-dia has 5 independent anisotropy parameters Pand S -wave velocities and three anisotropic pa-rameters epsilon, delta and gamma as defined byThomsen(1986). This type of symmetry is mostof to observed in shales which constitute about75 percent of the clastic fill of sedimentary ba-sins around the world. Without going in to fur-ther details ofanisotropic parameters and their es-timation, the implication of anisotropy have beenshown in two examples (1) anisotropic imagingfor rock property indicators ( Martin, 2000) and(2) anisotropic 3D prestack depth migration(Hawkins et al., 2000). Fig.l5a shows a seismicsection with a colour overlay of anisotropy pa-rameter profile (eta, derived from combinationofepsilon and delta) for a known discovery overa graben in the west of Feroe-Shetland basin(Martin, 2000). The strong negative values arerepresented by blue and strong positive values

by red colours. The anisotropy values are stronglynegative for Basalt. The formation just above theBasalt shows low anisotropy. The flat spot andtop of the reservoir provide good definition oflow anisotropy zone. The bright spot at the topof Mid-Eocene either side of the reservoir ap-pears to be channels filled with shale. 3D prestackdepth migration was performed over a salt domefeature in the southern North Sea data set us ingisotropic velocities and anisotropic velocities invelocity models by Veritas DGC Inc. and Trans-canada of the Netherlands jointly. The anisotro-pic parameters were used during velocity pick-ing stage of the velocity/depth model buildingprocedure. Bothfhe processed sections are shownin Fig.(15b) ( Hawkins et al, 2000). The isotro-pic 3D PSDM performed with imaging veloci-ties is shown in the left of Fig. 15b and reveals asignificant mistie to the well. The right side plotof Fig. 15b shows that key formation tops in thewell now tie with the seismic at the correct depth.The image obtained from anisotropic velocitymodel is better focused and positioned. The de-rived velocity in the model matches with blockedvelocity from the well. Both these examplesclearly show that accounting for anisotropy inimaging can improve structural and lithologicalinformation derived from the seismic data.

Seismic Inversion:

Seismic inversion is a technique that ex-tract information about the physical propertiesof the subsurface from the observed seismic data.This of late has become an important tool in thegeophysicist’s arsenal. Inversion techniques arebeing used commonly for extraction of acousticimpedance from post stack seismic data. Correct-ing seismic data to zero phase prior to poststackinversion and induction of low frequencies afterinversion greatly enhances the lateral consistencyand interpretability of the seismic data. Acous-tic impedance (Al) is defined as the product ofrock density and P-wave velocity in one dimen-sional earth model. This means that Al is a rockproperty and not an interface property like seis-mic amplitude and amplitude attributes. As a re-sult. At makes sequence stratigraphic analysismore straight forward. Wavelet side lobes areattenuated, eliminating some false stratigraphic-


Fig 16 a. Interpreted 2-D seismic section

Source: Van Reil et al, 2000

like effects. Fig.l6a displays a partially inter-preted 2D seismic section (Van Reil, 2000). Onekey horizon (yellow event) has been identifiedfrom the well control on the left and right of thesection. Seismic section clearly shows that com-pleting the interpretation is difficult. Followingthe seismic events from left to right and right toleft leads to a skip of two cycles around themiddle of the section. Fig. 16b shows the inver-sion results of seismic section shown in Fig.l6aobtained by applying a modern broad band sparsespike ‘inversion algorithms. The reservoir hori-zon discussed above is now very easy to inter-pret. Acoustic impedance has been consideredas an ideal parameter for volume based interpre-tation and can be directly related to well control,allowing the use of porosity, saturation and li-thology logs to analyse these data. Elastic in-version is the latest advancement for converting

Fig 17: Schematic diagram of seismic inversion frompre-stack seismic data

Fig 16 b. Acoustic Impedence sectionSource: Van Reil et al, 2000

reflection amplitude into elastic impedance pro-file from prestack seismic data (Connoly, 1999,Verwest et al., 2000) . This is being practised inindustry through two approaches (1) linear in-version using layer stripping scheme and (2) non-linear iterative least square technique. Non-lin-ear techniques are being widely used for inver-sion because linear inversion is highly unstableand noise sensitive. Non-linear least square in-version minimises squared residual error betweenthe observed and computed seismic data for thelayered earth model considering plane source.The starting model gets updated iteratively withthe incremental update of the model parameters.Such approach is logically appealing, but it facesdifficulties due to inadequate robustness that re

Fig 18: Comparison of real and synthetic shot recordSource: Jin and Beydown, 2000

strict guess model to be in the closeneighbourhood of true model. Recent focus oninversion through global optimisation techniquessuch as simulated annealing, genetic algorithm,


taboo search etc. address substantial improve-ment in robustness of inversion which requireextensive computational efforts ( Sen and Stoffa,1995, Mallik, 1999, Mccormack et al., 1999). Aschematic diagram of seismic inversion fromprestack seismic data using global optimisationtechniques are given in Fig. 17. In carrying outnon linear inversion using global optimisationtechniques, a complete prestack elastic responsefor a given earth model is being generatedthrough forward modelling method at each CMPlocation. This complete elastic response includesprimary P-wave reflections, primary mode-con-verted wave reflections, interbed P-wave mul-tiple reflections, interbed multiple mode-con-verted wave reflections, the interference or tun-ing effects due to thin beds and transmission ef-fects through gradient zones for any laterally vari-able medium. This highly computer intensivecomputation of forward modeling is iterated un-til modelled elastic response satisfactorilymatches with the real shot record at that CMPlocation as is seen in Fig. 18 (Jin and Bedown,2000).

The generation of acoustic impedancevolume from normal impedance data and analo-gous elastic impedance volume from wide angledata maximises vertical and lateral resolution,

simplifies lithologic and stratigraphic definitions,supports static reservoir models, predictspetrophysical properties like Poisson’s ratio, po-rosity, clay content and net/gross pay throughout the seismic data volume.

Seismic Attribute Technology:

Seismic attribute technology (SeismicAttributology) has been advancing at a rapid paceand is the core of reservoir geophysics. This actsas a bridge linking exploration and productionreservoir aspects. A cluster of seismic attributescan be extracted from prestack and post stackseismic data forreseivoir mapping andcharacterisation. These attributes are not totallyindependent from each other but simply differ-ent ways of presenting and studying a limitedamount of basic information available in com-plex traces in the form of time, amplitude, fre-quency and attenuation. This has formed the ba-sis for attribute classification shown in Fig. 19(Brown, 1996, Chen and Sydney, 1997). Mostof the seismic attributes are derived from thepoststack amplitude volume of seismic data.Broadly, These attributes can be classified asgeometrical and physical, based on then- appli-cation in reservoir delineation andcharacterisation. Grid based attributes such as

Fig 19. Seismic attributes classification


Fig 20a. Coherency sliceSource: Gerztenkorn et al., 1999

Fig 20b. Dip/Azimuth plotSource: Gerztenkorn et al., 1999

Fig 20c. Seismic sectin along AA’Source: Gerztenkorn et al., 1999

Fig 20d. Seismic sectin along BB’Source: Gerztenkorn et al., 1999

Fig 21a. Time residual map showing channel featureSource: Srivastava et al, 1999

Fig 21b. Average Inst. Frequency map showing channelfeature

Source: Srivastava et al, 1999


coherency , dip and dip-azimuth known as geo-metrical attributes are most suitable for determi-nation of geometrical characteristics of reser-voirs. These attributes highlight the spatial pat-terns such as faults and facies discontinuities, butcan not be directly related from the logged reser-voir properties like porosity and thickness. Anexample of coherency and dip-azimuth attributesfor delineating tectonic features from an offshoreTrinidad 3-D survey are shown in Figs.20 (a,b,cand d) ( Gersztenkom et al.,1999, Shirley,2000).The coherency slice inFig.20a shows a series ofmore or less, northwest-southeast faults. Exten-sional forces oriented roughly northeast-south-west are responsible for these fault trends. Thedip/azimuth plot shown in Fig.20b indicates thatdips increase in an easterly direction (as evi-denced by the brightening of the red and megentacolours), with maximum dips observed along thenorthwest-southeast fault on the eastern side. Thereflectors dip in a north-north easterly direction.The seismic cross section AA’ shown in Fig.20cruns parallel to the faults. Cross section BB’shown in Fig.20d reveals a series of faultedblocks and increase in dip near the right edge at1100msec. Both the cross sections suggest thatthe geologic history of the area is complex withboth compressional and extensional forces shap-ing the current structure. Sample or windowbased attributes computed from amplitude andfrequency are termed as physical attributes likereflection strength, RMS amplitude, total energy,instantaneous frequency, spectral bandwidth, arclength, instantaneous phase etc.,. The time re

Fig 22a. Relation between rock properties and seismicevents.

sidual and average instantaneous frequency mapsextracted from 3D seismic data volume ofCambay basin, India clearly shows the channelfeatures of thin and limited areal extent sandwhich can not be mapped by the conventionalinterpretation (Figs.21a, b, Srivastava etal.,1999). The seismic attributes derived from theprestack seismic data are velocity and AVO at-tributes which have already been discussed ear-lier. These Pro and post stack seismic attributescan be utilised in seismic interpretive process-ing, structural mapping, stratigraphic interpreta-tion, lithology prediction, reservoircharacterisation, simulation and monitoring..These attributes can also be used as direct hy-drocarbon, lithology, porosity and fluid indica-tors (Barnes, 1999). A well known Geoscientistand Pioneer in attribute technology Dr. M.TurhanTaner, Vice president. Rock Solid Images, USAhas expressed his views that “presently, attributesare being used to derive about 35 percent of theavailable information contained in the seismicdata. It will increase to 80 percent with in 10 yearswith the~advancementt in attribute technology”.

4D Seismic:

The production of hydrocarbons,alongwith other field development processes,change the physical properties of a reservoir overthe time. A logical extension of generating a staticreservoir model is to dynamically characterisethe reservoir. Time lapse 3D ( i.e„ 4D) seismicsurveying enables dynamic reservoir

Fig 22b. Possible seismic response change following time-lapse


characterisation and also allows to see thechanges in the dynamic properties of the reser-voir King, 1996). These dynamic changes are keyto the prediction of reservoir performance andthe design of improved recovery schemes. How-ever, non-uniform data acquisition techniques,old vintages of data and processing techniquesmakes the mapping of reservoir and evaluationof production induced changes in the reservoirdifficult. Despite the best efforts, time lapse seis-mic data acquisition is inherently non-repeatable.There are few factors, which can be, controlledsuch as acquisition geometry, field parametersand instrumentation, receiver arrays, etc.. Num-

ber of factors which can not be controlled arenear surface variations, sea state, water tempera-ture and salinity, source and streamer depths, re-ceiver coupling, geological factors - gas clouds,overburden collapse, residual multiple energy,ambient noise and acquisition obstacles (pipelines, platforms, well heads, pump house etc.).Careful processing of time lapse seismic canimprove repeatability of 4D seismic surveys, butbest survey results can be achieved from a pur-pose-designed survey only. It is necessary to un-derstand relations between rock properties andseismic reflection events at the boundaries be-fore analyzing seismic changes over time(

Fig 23. Comparison of Acoustic impedence at the top of Fulmar field(Central North Sea)Source: Johnson et al, 1998

Fig 24. Time lapse 4-D seismic monitoring (Norwegian North Sea)


Fig.22a, Jack, 1998). During hydrocarbon extrac-tion process, the changes in seismic responsecome either due to primary reservoir changespore fluid compositions ( saturation, viscosity,compressibilty, fluid type), pore pressure, tem-perature] or to secondary effects ( compaction,porosity, density, overburden, stress, fracturingdue to temperature reduction and water flood-ing, chemical changes) or both. Quantifying theeffect of these primary and secondary factors onseismic response through feasibility and sensi-tivity analysis allows us to determine before plan-ning a repeated seismic survey whether produc-tion associated changes can be in principle vis-ible from seismic (Fig.22b, Jack, 1998). Variousfactors such as pore pressure, saturation, tem-perature, salinity, pore fluid composition andproperties, reservoir thickness, dominant fre-quency and average resolution are required to beknown to forward model the seismic responseof a reservoir depending upon the recovery pro-cess. It also requires that data acquisition andprocessing to be repeatable so that the differencesbetween the two data sets can be relied as realchanges due to production. Seismic detection ofdynamic reservoir properties in space and timeis key to improved reservoir recoveiy while re-ducing risk and environmental impact.

A 3D time -lapse seismic case study ofFulmar field in the Central North Sea situated atabout 270km. of southeast of Aberdeen is shownin Fig.23 ( Johnson et al., 1998). This field wasunder production since 1982. Water is main drivemechanism supported by flank injection.Petrophysical analysis for this field indicated thatwater replacing oil will result in increase in seis-mic impedance. The pressure decline due to pro-duction during the time between two seismicsurvey will further increase the seismic imped-ance. These impedance changes are clearly ob-served between two seismic surveys conductedin 1977 and 1992. The seismic differences ob-served between 1977 and 1992 surveys werehighly useful in placement of additional wellsand in identifying the areas of bypassed oil. An-other case study of 3D time-lapse seismic is ofGullfaks field situated on the western margin ofthe North Viking Graben in the Norwegian NorthSea ( Beamer et al., 1996). Saturation Modelling

was performed toderive changes in P-wave ve-locity, S-wave velocity and impedance. Model-ling results show that for a saturation change from10% to 80% P-wave velocity has changed 12%,ratio of P to S velocity 12% and acoustic imped-ance by 13%. The effect of pressure and tem-perature change on P to S velocity ratio was in-significant. Acoustic impedance map derivedfrom two seismic surveys conducted in 1985 and1995 clearly show how the fluid distribution ischanged as field produces after waterflooding(Fig. 24). Assessment of actual drainage patternhas helped reservoir engineers to optimise andmanage the reserve recovery from this field.

Advances in Information Technology:

Today, it is difficult to imagine what theworld was like without the internet. This mightseem to be a humorous overstatement to thoseof us who have lived through the transition. Butto future generations, a pre-intemet world willseem as remote as the time before computers orjet air travel seems to us. Even today, in its in-fant state, the internet is the largest library, book-store, auction house and art gallely in the world.Impact of e-commerce is among many signifi-cant paradigm shifts in E & P industry inrecenttimes. The adoption of rapidly evolving internet/intranet infrastructure and platform independentprogramming languages is allowing companiesto take advantage of the flexibility and technol-ogy -leverage inherent in this new informationparadigm. Internet technology has reached “criti-cal mass” faster than any other new technologyin recent times by reaching to more than seventymillion users in just five years. The energy sec-tor alone has spent more than five billion dollarson internet technologies from 1999 onwards.Companies are already using internet for effec-tive management communications, collaborativebusiness partnerships and projects. The compa-nies have established efforts to access, share, anddistribute well and seismic data over the internet.EPINET or Exploration and Production Informa-tion NET working is one such maiden effort onthe part of ONGC under technical expertise fromSchIumberger-Geoquest to integrate all its E&Pdata to form a validated Corporate E& P data-base with secured access. The data base includes


data classes like general well data, geologicalwell data, seismic 2D/3D navigation data, seis-mic Interpretation data, production data, cultural,geopolitical data, lease and concession data, anygrided data. The data generated at different re-gions and work centres of ONGC is transmittedin real time through wide and local area networksto the corporate data base. The potential ofinternet based seismic processing is significantbecause it makes computer intensive technolo-gies accessible to a large community of users,while providing an efficient resource distributionand allocation to all potential users requiringaccess to high performance computing facilitiesand state-of-the-art software ( Bevc, et al., 2000).Computing resources for production processingand imaging of seismic data are outsourced byseveral major oil companies for both routine pro-cessing and research. Access to these applica-tions are usually being provided via a fast dedi-cated network connection. Internet processingcan speed up processing turn -around time andoptimise results because it allows the interactionof interpreters at all stage of processing. This isveiy helpful specially in high quality depth im-aging where interpretation input can be very criti-cal to obtain the best depth image. Further, trans-mission of seismic data via satellite representsan opportunity to revolutionise the performanceof overall seismic industry from acquisition ves-sel to onshore processing centre, early deliveryof processed data to the clients in coming years(Aylors et al., 2000).

Reservoir Characterisation:

Reservoir characterisation is an impor-tant aspect that integrates information from dif-ferent disciplines (geology, geophysics,geochemistry and petroleum engineering) forproviding a more complete description of thephysical properties of a reservoir. True integra-tion of data, knowledge and disciplines is a keyarea for more complete reservoir characterisation.The geoscientist has a variety of measurementsto characterise the reservoir. Some such asgravimetry are sensitive to volumetric param-eters; other such as sonic logging are essentiallyline integrals that are sensitive to propagationparameters( velocity or slowness). However,

methods that use reflected signals detect bound-aries directly, because the discontinuity itself gen-erates the reflection. These methods include someacoustic measurements (surface and boreholeseismics) together with less widely used tech-niques like ground penetrating radar and provideresolution ranging from 0.1m to 100m and moredepending upon their source-receiver geometryand recording frequency content. A schematicrepresentation of the range and resolution avail-able from different acoustic methods shown inFig. 25 clearly depicts the importance of dataintegration (Esmersoy et al., 1998). The resolu-tion is typically controlled by the frequency band-width of the received signal. The maximum range

Fig 25. Schematic representation of the range and resolu-tion available from different seismic methods in differentscales


of each method is primarily controlled by the sig-nal attenuation that increases rapidly with fre-quency. The minimum range is determined bythe resolution limit and the source –receiver ge-ometry. The integration of data, knowledge anddisciplines has to take place at different levels.

Multidisciplinaiy approaches that involveintegrating data and intelligence of differenttypes, scales, uncertainties and resolutions for re-ducing risk will be more of a necessity than asimple corporate buzzword. The walls buildaround classical disciplines such as reservoirengineering, geology, geophysics and geochem-istry are becoming more permeable. The database, data fusion and data mining methodologieswill have to cut across various disciplines. Con-sequently, today’s integration which is based onthe integration of results will give way to newform of integration: The Integration of Disci


Fig 26: Distinction between integration of discipline andintegration of results.

Source: Aminzadeh, 1996

plines and Knowledge as shown in Fig.26 clearlyshows the difference between traditional ap-proach of results integration and more desirableintegrated approach among different disciplinesat a much earlier stage(Amin Zadeh, 1996). Ide-ally these integration techniques will be equippedto handle data fusion problems with data setsinvolving wide range uncertainties and scales.

Achieving the true integration objectives willrequire professionals with working cross- disci-plinary knowledge, and perhaps many more gen-eralists than now available. According to Dr.M.Turhan Taner, Vice president. Rock solid Im-ages, USA “Geophysicists, Geologists and en-gineers must continue to learn each others dis-ciples and requirements if we are to see trulyintegrated and effective asset team” ( FirstBreak, 2000c).

3-D earth modelling is key to exploringand producing complex reservoirs (Pramanik etal., 1999). The industry needs both modellingtechniques and softwares fulfilling specific re-quirements as well as disciplinary methodolo-gies and products for integrated studies. All thegeophysical, geological and geochemical datacontributes to the understanding of the same field,therefore cross analysis and validation through a3-D shared earth model improve the model qual-ity. Introducing the 3-D elastic modelling fromthe beginning of the project improves the under-standing and the quality of the reservoir model.3-D modelling integrates information that can beused for computing volumetrics. The benefit ofsuch an approach is to improve the quality of themodel by generating a model consistent with theavailable cross disciplinary data. If a model is

Fig 27. Available visualization environment and thier uses in Petroleum Industry


consistent with structural, sedimentaiy and res-ervoir data, it has a higher probability for beingrepresentative of the reservoir. Such a model isknown as earth shared model which is used asthe reference for estimating uncertainties. To fullybenefit from 3 D modeling, te model is to becompared and updated with new information assoon as it is available.

Advances in 3D Visualization andImmersive Technology:

The final and most important area of tech-nology development is advanced 3Dvisualisation techniques. 3D visualization is amethod of seismic interpretation in which theseismic reflectivity of the subsurface is directlyevaluated in three dimensional space by apply-ing various levels of transparency to the data (Kidd, 1999). Advanced visualization tools andimmersive 3D visualisation technology allowmore effective data representation, integration ofdifferent data types and increased productivityof multidisciplinary teams. A variety ofvisualisation environments are available in thepetroleum industry and it is up to the individualorganization to assess and implement the one thatmeets organisational and budgetary requirements(Fig. 27, Hanley, 1999). Some of them offer col-laborative experience, some other deliver theimmersive experience and few others offer both.Personal display devices include Fakespace’sBoom and Fakespace’s Push3C. These environ-ments offer a high degree of immersion but foronly a single user and interaction with data isdifficult. Small collaborative environments (e.g.’the Fakespace VersaBench and The Workbenchand 4m Vision Dome) offer a portable immersiveand collaborative environment for a small num-ber of users, such as an asset team. Presentationenvironments (such as reality centres) andWorkWall are effective for displaying data, givehigh resolution, and accommodate large audi-ences. The Cave environment offers closest thingto complete immersion. These virtual reality(VR)and immersive environments have leaped to theforefront in the energy industry, and their use/bygeoscientists and engineers is galloping. VR isdefined as “A computer generated artificial worldin which the users are immersed and where one

can navigate and interact with objects in an in-tuitive and natural manner “. VR and immersiveenvironment create illusion of being in a realworld. Individuals are surrounded by the data andactually feel they are part of it. Geoscientists canlook into data and interpretations in great detailsand understand the spatial relationships in threedimensions. The enlarged size and extent of theimages in these environments allow interpretersto see details in geologic data without lootingregional perspective.

Conclusions:

An overview of various practical E & Pproblems and their possible solutions throughintegration of state-of- the-art geophysical tech-nologies have been described here. The adop-tion and effective implementation of these newlyemerged technologies in a integrated way haveprovided more and more reliable information forinterpreting subsurface structures, complex strati-graphic and lithologic features to define the ac-curate reservoir models for use in drilling strate-gies, estimating inplace and recoverable reserves.They have reduced risk, cost and cycle time, en-hanced recovery factor and yields, improved riskassessment and have created new E& P businessgrowth opportunities. The integration of thesegeophysical technologies with different scales ofdata, cross disciplines and knowledge may inturnresult in minimising the gap between demand andsupply of petroleum and adhere to the energysecurity concern of the nations.

Acknowledgments:

Authors are grateful to Oil and naturalGas Corporation limited, India for providing thenecessary information and infrastructural facili-ties to canyout this work. Authors are thankfulto Shri YB. Sinha, Director exploration), ONGCfor approving this work to present as a keynotepaper in PETROTECH-2001 held during Janu-ary 9-11 at New Delhi.

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Geophysical Technology Integration in Hydrocarbon ... · and innovations in seismic related technologies are proving to be more important in the develop-ment of oil and gas fields