Estimation of effective porosity using geostatistics and multiattribute transforms: A case study

The middle Eocene Kalol Formation in the north Cambay Basin of India is producing hydrocarbons in commercial quantity from a series of thin clastic reservoirs. These reservoirs are sandwiched between coal and shale layers, and are discrete in nature. The Kalol Formation has been divided into eleven units (K‐I to K‐XI) from top to bottom. Multipay sands of the K‐IX unit 2–8 m thick are the main hydrocarbon producers in the study area. Apart from their discrete nature, these sands exhibit lithological variation, which affects the porosity distribution. Low‐porosity zones are found devoid of hydrocarbons. In the available 3D seismic data, these sands are not resolved and generate a composite detectable seismic response, making reservoir characterization through seismic attributes impossible. After proper well‐to‐seismic tie, the major stratigraphic markers were tracked in the 3D seismic data volume for structural mapping and carrying out attribute analysis. The 3D seismic volume was inverted to obtain an aco...

[1]  A. Francis.  Acoustic impedance inversion pitfalls and some fuzzy analysis , 1997 .

[2]  D. Oldenburg,et al.  Inversion of band-limited reflection seismograms: Theory and practice , 1986, Proceedings of the IEEE.

[3]  Jiaqi Liu,et al.  Seismic-controlled nonlinear extrapolation of well parameters using neural networks , 1998 .

[4]  Alistair R. Brown.  Color in seismic display , 2001 .

[5]  Well log prediction using attributes from 3C–3D seismic data , 1998 .

[6]  Rafael E. Banchs,et al.  From 3D seismic atrributes to pseudo-well-log volumes using neural networks: Practical considerations , 2002 .

[7]  Mrinal K. Sen,et al.  Global Optimization Methods in Geophysical Inversion , 1995 .

[8]  F. Romberg,et al.  A geological and geophysical study of Pilot Knob (South), Travis County, Texas , 1954 .

[9]  Donald F. Specht,et al.  Probabilistic neural networks , 1990, Neural Networks.

[10]  P. Schultz,et al.  Seismic-guided estimation of log properties; Part 1, A data-driven interpretation methodology , 1994 .

[11]  Donald F. Specht,et al.  A general regression neural network , 1991, IEEE Trans. Neural Networks.

[12]  D. B. Neff.  Estimated pay mapping using three-dimensional seismic data and incremental pay thickness modeling , 1990 .

[13]  H. Trappe,et al.  Using neural networks to predict porosity thickness from 3D seismic , 2000 .

[14]  R. Tonn.  Neural network seismic reservoir characterization in a heavy oil reservoir , 2002 .

[15]  Brian Russell,et al.  Combining geostatistics and multiattribute transforms - A channel sand case study , 2001 .

[16]  S. Biswas.  Regional tectonic framework, structure and evolution of the western marginal basins of India , 1987 .

[17]  James S. Schuelke,et al.  Reservoir architecture and porosity distribution, Pegasus Field, West Texas – an integrated sequence stratigraphic–seismic attribute study using neural networks , 1997 .

[18]  S. Mallick.  Some practical aspects of prestack waveform inversion using a genetic algorithm: An example from the east Texas Woodbine gas sand , 1999 .

[19]  Gedeon Dagan,et al.  Statistical Inference of Spatial Random Functions , 1986 .

[20]  P. Schultz,et al.  Seismic‐guided estimation of log properties (Part 3: A controlled study) , 1994 .

[21]  R. Carpi,et al.  POROSITY PREDICTION FROM SEISMIC DATA , 1982 .

[22]  Bruce S. Hart,et al.  Comparison of linear regression and a probabilistic neural network to predict porosity from 3‐D seismic attributes in Lower Brushy Canyon channeled sandstones, southeast New Mexico , 2001 .

[23]  Quincy Chen,et al.  Seismic attribute technology for reservoir forecasting and monitoring , 1997 .

[24]  Shuki Ronen,et al.  Seismic‐guided estimation of log properties (Part 2: Using artificial neural networks for nonlinear attribute calibration) , 1994 .

[25]  John Quirein,et al.  Use of multiattribute transforms to predict log properties from seismic data , 2001 .

[26]  R. O. Lindseth.  Synthetic sonic logs; a process for stratigraphic interpretation , 1979 .

[27]  John Quirein,et al.  Multiattribute seismic analysis , 1997 .

[28]  Alistair R. Brown.  Understanding seismic attributes , 2001 .

[29]  R. F. Stoisits,et al.  Applications of genetic algorithms in exploration and production , 1999 .

[30]  Joel Walls,et al.  Seismic reservoir characterization of a U.S. Midcontinent fluvial system using rock physics, poststack seismic attributes, and neural networks , 2002 .

[31]  O. Dubrule.  Geostatistics In Petroleum Geology , 1998 .

[32]  Alistair R. Brown.  Data polarity for the interpreter , 2001 .

[33]  Philippe Marie Doyen,et al.  Porosity from seismic data: A geostatistical approach , 1988 .

[34]  A. Sena,et al.  Elastic Impedance Inversion , 2000 .