An Integrated Technique for Production Data Analysis (PDA) With Application to Mature Fields

Abstract

Summary The most common data that engineers can count on, especially in mature fields, is production rate data. Practical methods for production data analysis (PDA) have come a long way since their introduction several decades ago and fall into two categories: decline curve analysis (DCA) and type curve matching (TCM). DCA is independent of any reservoir characteristics, and TCM is a subjective procedure. State of the art in PDA can provide reasonable reservoir characteristics, but it has two shortcomings: First, for reservoir characterization, the process requires bottomhole or wellhead pressure data in addition to rate data. Bottomhole or wellhead pressure data are not usually available in most of the mature fields. Second, a technique that would allow the integration of results from hundreds of individual wells into a cohesive fieldwide or reservoirwide analysis for business decision making is not part of today's PDA tool kit. To overcome these shortcomings, a new methodology is introduced in this paper that has three unique specifications: It does not "require" pressure data, bottomhole or wellhead (but it can make use of it, if available, to enhance accuracy of results). It integrates DCA, TCM, and numerical reservoir simulation or history matching (HM) to iteratively converge to a near unique set of reservoir characteristics for each well. It uses fuzzy pattern recognition technology to achieve fieldwide decisions from the findings of the analysis.