A Screening Methodology for the Optimal Selection of AL Methods for Geothermal Wells

Abstract

Well-flow rates significantly influence the economic viability of geothermal projects. Geothermal wells targeting natural fractures typically yield high flow rates; however, the production performance of these wells can substantially decline over time. Artificial lift (AL) methods, including gas lift (GL) and downhole pumps such as Electrical Submersible Pumps (ESPs) and line shaft pumps (LSPs), are effectively used to compensate for production losses in geothermal wells. This study presents a screening and decision-making methodology to determine the most suitable AL method for geothermal wells with different characteristics, considering a techno-economic analysis of the various lift methods. A Python scrpt was developed to automate the selection of an optimal AL method using a structured decision-making approach including Boolean logic analysis and Multicriteria Decision Analysis (MCDA) methods.