Evaluation of a Statistical Method for Assessing Infill Production Potential in Mature, Low-Permeability Gas Reservoirs

[+] Author and Article Information
L. Guan

ChevronTexaco, 4800 Fournace Place, Room E537, Bellaire, TX 77401  

D. A. McVay

Department of Petroleum Engineering, Texas A&M University, 3116 TAMU, College Station, TX 77843-3116  

J. L. Jensen

Department of Petroleum Engineering, Texas A&M University, 3116 TAMU, College Station, TX 77843-3116  

G. W. Voneiff

MGV Energy, #2000 125-9th Ave SE Calgary, AB Canada T2G 0P8

J. Energy Resour. Technol 126(3), 241-245 (Oct 19, 2004) (5 pages) doi:10.1115/1.1781672 History: Received December 11, 2003; Revised June 17, 2004; Online October 19, 2004
Copyright © 2004 by ASME
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Grahic Jump Location
Largest heterogeneity permeability distribution (Case 4) used for the simulation and MMWM testing. Scale is in md (10−3 μm2). The small white circles are the locations of the 100 wells. Cases 2 and 3 distributions have less variability but longer correlation lengths.
Grahic Jump Location
Distributions of well spacing and date of first production for the 100 wells.
Grahic Jump Location
Comparison of the infill well maximum production predictions from simulation and MMWM for Case 4 shows MMWM performing poorly in this highly heterogeneous reservoir
Grahic Jump Location
Variability of difference between MMWM and simulation infill potential estimates decreases as number of wells, N, increases. Lines are least-squares fit to points and all have insignificant non-zero Y-axis intercepts at the 90% level. Values in parenthesis are the line slopes.




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