Documentation and quantification of velocity anisotropy in shales using wireline log measurements

Brevik, Ivar; Ahmadi, Gholam Reza; Hatteland, Trude; Rojas, María Alejandra

doi:10.1190/1.2715048

Cited by 20 publications

(17 citation statements)

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“…In situ estimates of anisotropy in shales can be made by comparing sonic velocities in wells that have different deviations but pass through the same formation (Furre and Brevik, 1998;Hornby et al, 1999Hornby et al, , 2003Brevik et al, 2007;Walsh et al, 2007;Keir et al, 2011). However, such estimates also will be affected by lateral heterogeneity in the formation of interest because different wells sample the formation at different areal locations.…”

Section: Introductionmentioning

confidence: 97%

Anisotropy estimate for the Horn River Basin from sonic logs in vertical and deviated wells

et al. 2015

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Shale anisotropy must be quantified to obtain reliable information about reservoir fluids, lithology, and pore pressure from seismic data. Failure to account for anisotropy in seismic processing can lead to errors in normal moveout (NMO), dip moveout (DMO), migration, time-to-depth conversion, and amplitude variation with offset (AVO) analysis. Kriged estimates of density, vertical compressional-wave, and shear-wave velocities were derived from vertical wells in an area of interest in the Horn River resource play in northeastern British Columbia. The kriged predictions were compared with measured logs along the trajectory of a deviated well. Whereas the density comparison provided a blind test of kriging accuracy because density is scalar and independent of well deviation, the same comparison for sonic velocities revealed that they are systematically higher than the kriged vertical velocities. This difference was used to estimate anisotropy parameters at the location of the deviated well. The fact that the higher velocities observed are caused by anisotropy was confirmed subsequently by using the derived anisotropy parameters to apply a nonhyperbolic moveout correction to flatten gathers from a seismic survey 10 km north of the area of interest, within which the anisotropy parameters were estimated.

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Section: Introductionmentioning

confidence: 97%

Anisotropy estimate for the Horn River Basin from sonic logs in vertical and deviated wells

et al. 2015

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“…With increased focus on cross-disciplinary integration, geophysicists are starting to incorporate this geological knowledge into the modelling and analysis of geophysical data (e.g. Draege et al 2006, Brevik et al 2007, Mondol et al 2007). As with sands, we can distinguish between depositional and diagenetic trends in shales.…”

Section: Rock Physics and Depositional Trendsmentioning

confidence: 99%

Explorational Rock Physics – The Link Between Geological Processes and Geophysical Observables

Avseth

2010

Petroleum Geoscience

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The field of rock physics represents the link between qualitative geological parameters and quantitative geophysical measurements. Increasingly over the last decade, rock physics has become an integral part of quantitative seismic interpretation and stands out as a key technology in petroleum geophysics. Ultimately, the application of rock physics tools can reduce exploration risk and improve reservoir forecasting in the petroleum industry.This chapter covers basic rock physics principles and practical recipes that can be applied in the field. The importance and benefit of linking rock physics to geological processes, including depositional and compactional trends, is demonstrated. It is further documented that lithology substitution can be of equal importance to fluid substitution during seismic reservoir prediction. It is essential in exploration and appraisal to be able to extrapolate away from existing wells, taking into account how the depositional environment changes, together with burial depth trends. In this way rock physics can better constrain the geophysical inversion and classification problem in underexplored marginal fields, surrounding satellite areas, or in new frontiers.Finally, practical examples and case studies are presented to demonstrate a best-practice workflow and associated limitations and pitfalls. Rock physics models are combined with well log and pre-stack seismic data, sedimentological information, inputs from basin modelling and statistical techniques, to predict reservoir geology and fluids from seismic amplitudes.P. Avseth ( ) Odin Petroleum, Bergen; NTNU, Trondheim, Norway e-mail: pavseth@yahoo.com Quantitative Seismic Interpretation Using Rock PhysicsThe main goal of conventional, qualitative seismic interpretation is to recognise and map geological elements and/or stratigraphic patterns from seismic reflection data. Often hydrocarbon prospects have been defined and drilled entirely on the basis of this qualitative information. Today, however, quantitative seismic interpretation techniques have become common oil industry tools for prospect evaluation and reservoir characterisation. The most important of these techniques include post-stack amplitude analysis (brightspot and dim-spot analysis), offset-dependent amplitude analysis (AVO-analysis), acoustic and elastic impedance inversion, and forward seismic modelling. These techniques seek to extract additional information about the subsurface rocks and their pore fluids from the reflection amplitudes and, if used properly, they open up new doors for the seismic interpreter. Seismic amplitudes primarily represent contrasts in elastic properties between individual layers and contain information about lithology, porosity, pore fluid type and saturation, as well as pore pressure -information that cannot be gained from conventional seismic interpretation. Seismic amplitude maps are increasingly important in prospect evaluation and reservoir delineation. As shown in Fig. 18.1, the amplitude patterns often provide a good insight into depo...

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“…Alternative sources of information about elastic properties and elastic anisotropy in shales are sonic logs in deviated wells, walk‐away vertical seismic profiles, and wide‐angle seismic data carefully processed to obtain elastic anisotropy (e.g., Gaiser ; Brevik et al . ; Grechka ). The most complete database that embraces both laboratory and larger scale sonic and seismic measurements of elastic properties in shales was put together by Horne ().…”

Section: Database On Elastic Properties In Shaly Formationsmentioning

confidence: 99%

Compaction trend versus seismic anisotropy in shaly formations

Pervukhina

Rasolofosaon

2017

Geophysical Prospecting

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Shales comprise more than 60% of sedimentary rocks and form natural seals above hydrocarbon reservoirs. Their sealing capacity is also used for storage of nuclear wastes. The world's most important conventional oil and gas reservoirs have their corresponding source rocks in shale. Furthermore, shale oil and shale gas are the most rapidly expanding trends in unconventional oil and gas. Shales are notorious for their strong elastic anisotropy, i.e., so‐called vertical transverse isotropy. This vertical transverse isotropy, characterised by a vertical axis of invariance, is of practical importance as it is required for correct surface seismic data interpretation, seismic to well tie, and amplitude versus offset analysis. A rather classical paradigm makes a clear link between compaction in shales and the alignment of the clay platelets (main constituent of shales). This would imply increasing anisotropy strength with increasing compaction. Our main purpose is to check this prediction on two large databases in shaly formations (more than 800 samples from depths of 0–6 km) by extracting the major trends in the relation between seismic anisotropy and compaction. The statistical analysis of the database shows that the simultaneous increase in density and velocity, a classical compaction signature, is quite weakly correlated with the anisotropy strength. As a consequence, compaction can be excluded as a major cause of seismic anisotropy, at least in shaly formations. Also, the alignment of the clay platelets can explain most of the anisotropy measurements of both databases. Finally, a method for estimating the orientation distribution function of the clay platelets from the measurement of the anisotropy parameters is suggested.

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Documentation and quantification of velocity anisotropy in shales using wireline log measurements

Cited by 20 publications

References 0 publications

Anisotropy estimate for the Horn River Basin from sonic logs in vertical and deviated wells

Anisotropy estimate for the Horn River Basin from sonic logs in vertical and deviated wells

Explorational Rock Physics – The Link Between Geological Processes and Geophysical Observables

Compaction trend versus seismic anisotropy in shaly formations

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