A Decision Analytic Approach to Geosteering Operations

Abstract

Summary The technique of geosteering has been widely adopted in the petroleum industry for proper wellbore positioning. The benefits of geosteering have become more pronounced as drilling environments have become more complex. Geosteering-related technologies, such as downhole information-gathering tools and real-time data-transmission and data-analysis applications, have been continuously and significantly improved to support geosteering decisions. However, the full value of these advancements has yet to be realized. Because of uncertainties in predrill geological models, information gathered while drilling is applied in making real-time reservoir-navigation decisions. To achieve an optimal result requires a series of high-quality decisions regarding well-trajectory adjustment. Interestingly, geosteering-related literature does not demonstrate that the industry has applied a logically consistent approach for making geosteering decisions. Common practice, as described in the literature, does not clearly and quantitatively state measurable objectives, key underlying uncertainties, or relevance between underlying uncertainties and real-time information. Furthermore, it is unclear how a specific geosteering decision is being reached. Lacking a systematic and transparent framework for supporting geosteering decisions, the current approach is unlikely to result in optimal decisions for placing the well in the best possible location.1 In this paper, we introduce and discuss a decision-driven approach to the geosteering process. The main contributions of the paper are threefold: (1) a review of 46 SPE papers on geosteering, including a discussion of the main features of current geosteering methods; (2) the development and discussion of a decision analytic framework to support high-quality geosteering decisions; and (3) implementation of Bayesian inference techniques to consistently update ahead-of-the-bit reservoir uncertainties while behind-the-bit data are gathered in real time. The new framework relates real-time information to the key reservoir uncertainties and provides an unbiased and consistent approach for making high-quality geosteering decisions.