Review of Statistical Methods Used in Enhanced-Oil-Recovery Research and Performance Prediction

摘要

Recent literature in the field of enhanced oil recovery (EOR) was surveyed to determine the extent to which researchers in EOR take advantage of statistical techniques in analyzing their data. In addition to determining the current level of reliance on statistical tools, another objective of this study is to promote by example the greater use of these tools. To serve this objective, the discussion of the techniques highlights the observed trend toward the use of increasingly more sophisticated methods and points out the strengths and pitfalls of different approaches. Several examples are also given of opportunities for extending EOR research findings by additional statistical manipulation. The search of the EOR literature, conducted mainly through computerized data bases, yielded nearly 200 articles containing mathematical analysis of the research. Of these, 21 were found to include examples of statistical approaches to data analysis and are discussed in detail in this review. The use of statistical techniques, as might be expected from their general purpose nature, extends across nearly all types of EOR research covering thermal methods of recovery, miscible processes, and micellar polymer floods. Data come from field tests, the laboratory, and computer simulation. The statistical methods range from simple comparisons of mean values to multiple non-linear regression equations and to probabilistic decision functions. The methods are applied to both engineering and economic data. The results of the survey are grouped by statistical technique and include brief descriptions of each of the 21 relevant papers. Complete abstracts of the papers are included in the bibliography. Brief bibliographic information (without abstracts) is also given for the articles identified in the initial search as containing mathematical analyses using other than statistical methods.