Enhancing Geothermal Well Workover Planning Through Data-Driven Performance Evaluation

Abstract

Workover duration planning holds significant importance in minimizing non-productive time and preventing cost overruns. To achieve the optimal operational duration, it is imperative to acquire data pertaining to previous workover performances. This data encompasses various aspects, including the type and size of scaling, the length of the damaged casing, and the speed of the workover tool. By considering the similarity of well characteristics and challenges encountered, the distribution of this data can substantially enhance the success of workover planning. Regrettably, most often, the distribution of this data has not been adequately documented, resulting in heightened uncertainty and suboptimal workover planning. This, in turn, can adversely affect the accuracy of workover duration projections and overall operating costs. A preliminary dataset of workover parameter durations is established based on the analysis of workover data encompassing the liquid-dominated field in Central Java. This paper strives to refine workover planning practices by collating a comprehensive workover database encompassing the liquid-dominated field in Central Java and fields exhibiting analogous characteristics. Through this endeavor, a substantial enhancement in the precision of workover planning is anticipated, contributing to heightened operational efficiency and improved cost-effectiveness.