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Featured researches published by William W. Weiss.


SPE Annual Technical Conference and Exhibition | 1999

Producing GOR Used to Predict Permeability Distribution in a Tight Heterogeneous Reservoir

S. Wo; William W. Weiss; Robert Balch; J. Roe; R.P. Kendall

Production from tight reservoirs can yield flow pressures around the wellbores that are below the bubblepoint. The accumulation of free gas around the wellbores results in a rapid increase in the producing gas-oil ratio (GOR). This paper investigates the sensitivity of depletion-drive GOR to variations in permeability. A public domain, black oil simulator was modified to automatically estimate the permeability from GOR histories. The method presented in this paper is especially useful when interpretable pressure transient tests are not available and can be adapted to existing simulators without changing the core code. A multi-objective, simultaneous bisection algorithm was developed to provide automatic GOR history match and to predict permeability distributions. Following each iterative simulation run, the permeability-searching intervals for all of the wells were simultaneously reduced by half and the permeability distribution map was updated. The updated searching intervals are uniquely determined because the permeability-GOR correlation is monotonic. Usually a satisfactory match is obtained within 10 simulation runs, which is much more efficient than the gradient or stochastic methods typically used for an automatic history matching procedure. This method was applied to field data from the South Bisti Gallup Pool. Well communication tests have shown a strong permeability preference for a southwest-northeast orientation in the pools two tight pay zones. The automatic GOR match was applied to the 14-year depletion history of 52 wells. First, the ratio of K g /K o was estimated from the total field GOR match. Then, the local variation of permeability was determined according to the GOR history of the wells. Two perpendicular- oriented permeability distributions were obtained. This new method should be valuable for other low permeability reservoirs.


SPE/DOE Improved Oil Recovery Symposium | 2002

How Artificial Intelligence Methods Can Forecast Oil Production

William W. Weiss; Robert Balch; Bruce A. Stubbs


AAPG Memoir | 1998

Advanced Reservoir Characterization for Improved Oil Recovery in a New Mexico Delaware Basin Project

F. David Martin; Richard P. Kendall; Earl M. Whitney; Bob A. Hardage; Brace A. Stubbs; Bruce J. Uszynski; William W. Weiss


SPE/DOE Improved Oil Recovery Symposium | 2002

Regional Data Analysis to Better Predict Drilling Success: Brushy Canyon Formation, Delaware Basin, New Mexico

Robert Balch; D.M. Hart; William W. Weiss; Ronald F. Broadhead


Other Information: PBD: 6 Mar 2003 | 2003

RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

William W. Weiss; Ronald F. Broadhead; William R. Mundorf


SPE Permian Basin Oil and Gas Recovery Conference | 2001

Estimating Bulk Volume Oil in Thin-Bedded Turbidites

William W. Weiss; B.A. Stubbs; Robert Balch


SPE Annual Technical Conference and Exhibition | 2003

Simulated Expert Interpretation of Regional Data to Predict Drilling Risk

Robert Balch; William W. Weiss; T. Ruan; S. Weber


SPE Permian Basin Oil and Gas Recovery Conference | 2000

Time-to-Depth Conversion of Nash Draw "L" Seismic Horizon using Seismic Attributes and Neural Networks

D.M. Hart; Robert Balch; William W. Weiss; S. Wo


SPE Permian Basin Oil and Gas Recovery Conference | 2000

Predicting Core Porosity using Wire-Line Logs at Dagger Draw Field, SE New Mexico

Robert Balch; William W. Weiss; S. Wo; D. Welch


Other Information: PBD: 24 Oct 2000 | 1999

Risk Reduction with a Fuzzy Expert Exploration Tool

William W. Weiss

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Robert Balch

New Mexico Institute of Mining and Technology

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Bruce A. Stubbs

University of Texas at Austin

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Bruce J. Uszynski

University of Texas at Austin

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Earl M. Whitney

Los Alamos National Laboratory

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Richard P. Kendall

Los Alamos National Laboratory

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Bob A. Hardage

University of Texas at Austin

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S. Wo

New Mexico Institute of Mining and Technology

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Ronald F. Broadhead

New Mexico Institute of Mining and Technology

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D.M. Hart

Sandia National Laboratories

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R.P. Kendall

Los Alamos National Laboratory

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