Gas infill well selection using rapid inversion methods
Conference Paper
Overview
Additional Document Info
View All
Overview
abstract
It is often difficult to quantify the drilling and recompletion potential in producing gas fields, due to large variability in rock quality, well spacing, and well completion practices, and the large number of wells involved. Given the marginal nature of many of these fields, it is often prohibitively expensive to conduct conventional reservoir characterization and simulation studies to determine infill potential. There is a need for rapid, cost-efficient technology to evaluate infill potential in tight gas reservoirs. Some authors have used approximate, statistical methods, which are useful screening tools for identifying potential areas or groups of wells for further study. We present a new simulation-based inversion approach for rapid assessment of infill well potential. Our work differs from conventional simulation inversion applications in that, instead of focusing on small-scale, high-resolution problems, we focus on large-scale, coarse-resolution studies consisting of hundreds or thousands of wells. In an initial application, the method employs well locations, production data and an approximate reservoir description and, accordingly, is able to identify potential areas or groups of wells for infill development quickly and inexpensively. Prediction accuracy can be increased commensurate with reservoir characterization effort, time and costs. Thus, the method provides a consistent basis for transition from screening studies to conventional reservoir studies. The proposed approach is demonstrated to be more accurate than moving window statistical methods in synthetic cases, with comparable analysis times and costs. In a validation study of a field case with 40 years of production history, the method was able to accurately predict performance for infill wells in areas with sufficient production from existing wells to effectively quantify reservoir quality. 2004, Society of Petroleum Engineers Inc.
