Potential impacts of artificial intelligence expert systems on geothermal well drilling costs:

摘要

The Geothermal research Program of the US Department of Energy (DOE) has as one of its goals to reduce the cost of drilling geothermal wells by 25 percent. To attain this goal, DOE continuously evaluates new technologies to determine their potential in contributing to the Program. One such technology is artifical intelligence (AI), a branch of computer science that, in recent years, has begun to impact the marketplace in a number of fields. Expert systems techniques can (and in some cases, already have) been applied to develop computer-based ''advisors'' to assist drilling personnel in areas such as designing mud systems, casing plans, and cement programs, optimizing drill bit selection and bottom hole asssembly (BHA) design, and alleviating lost circulation, stuck pipe, fishing, and cement problems. Intelligent machines with sensor and/or robotic directly linked to AI systems, have potential applications in areas of bit control, rig hydraulics, pipe handling, and pipe inspection. Using a well costing spreadsheet, the potential savings that could be attributed to each of these systems was calculated for three base cases: a dry steam well at The Geysers, a medium-depth Imerial Valley well, and a deep Imperial Valley well. Based on the average potential savings to be realized, expert systems for handling lost circulations problems and for BHA design are the most likely to produce significant results. Automated bit control and rig hydraulics also exhibit high potential savings, but these savings are extremely sensitive to the assumptions of improved drilling efficiency and the cost of these sytems at the rig. 50 refs., 19 figs., 17 tabs.