Enhancing Decision Making in Critical Drilling Operations

Abstract

Abstract Many critical tasks in oil operations require cognitive skills for safe and efficient drilling. Oil well drilling is a complex process which frequently is leading to operational problems. One problem is wellbore cleaning. If the root cause of the problem was known, the treatment of the problem could be made more focused and efficient. However, to determine the root cause is difficult in this coupled process. One solution to this challenge is to apply knowledge intensive case based reasoning (KiCBR) methodology. KiCBR is a recent approach to problem solving and decision making where a new problem is solved by finding a set of similar previously solved problems, called cases, and reusing them in the new problem situation. This approach consists of two major parts: hierarchy of the concepts with different relation strength and case based reasoning. Concepts are abstracted to symbolic entities. Through the selected fields, data (real time logs, end of well plan and daily drilling reports, etc) are utilized to provide case data base. In this study, three main root causes were chosen; solids accumulation, problematic formation leading to future well cleaning and problematic formation causing well cleaning problems. This paper presents how to determine the root causes for poor hole cleaning episodes by means of the CBR (Case-Based Reasoning). All the involved parameters in each case were stored in the data base. Whenever an unexpected episode is encountered, highly similar case from the data base will come out for decision making. Furthermore, each case has specific and general lessons for those who are in charge of the operations. The match results were good enough but it needs to be improved through indicators that will reveal main cause more precisely.