An Automated Method of Matching Production Performance Using Dimensionless Solutions

Abstract

Abstract It is widely recognized that U.S. gas reserves can be substantially increased if gas from tight reservoirs can be more economically developed1,2. One of the main problems hindering the development of tight reservoirs is the general lack of adequate reservoir description. One of the best techniques for reservoir analysis is pressure buildup testing. In tight gas reservoirs, a buildup test which will adequately describe a large portion of the reservoir requires that a well be shut in for several weeks or months. Many operators run these long pressure buildup tests both before and after a well has been fracture treated. If such tests are run, an acceptable description of the reservoir and fracture can be obtained using reservoir simulation history-matching techniques3. Even when the pressure buildup tests are correctly run and interpreted, it is difficult to determine the areal extent of reservoir drainage. To determine drainage area, several years of production data are normally required. Therefore, to completely define a tight gas reservoir, the information obtained from the analysis of pre-fracture pressure buildup data, post-fracture pressure buildup data, and long-term production data must be combined4. The most important problem to be solved in the development of a tight gas reservoir is determination of the optimum fracture length. The optimum fracture length is a function of reservoir permeability, gas in place, and future net revenues and can best be quantified as a fraction of the drainage radius. To determine the optimum fracture length, it is necessary to predict future well performance as a function of effective propped fracture length. The effective areal extent of a reservoir must be known or estimated in order to accurately predict future well performance. Thus, knowledge of drainage area is critical in the determination of the optimum fracture length.