Automated Well Models Improve PCP Surveillance and Optimization

Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 207290, “Intelligent Operating Envelope Integrated With Automated Well Models Improves Assetwide Progressing-Cavity-Pump Surveillance and Optimization,” by Mohammed Al Sawafi and Antonio Andrade, Petroleum Development Oman, and Nitish Kumar, Weatherford, et al. The paper has not been peer reviewed. The operator has completed a project in which the progressing-cavity-pump (PCP) well-modeling process is automated. Models are built and sustained automatically in a well-management system (WMS) for all active PCP wells, with a major effect on day-to-day operational activities. The complete paper discusses use of physics-based well models from the WMS to automatically update operating envelopes (OE), identify daily oil-gain potential, and enable real-time PCP performance through a well-management-visualization system (WMVS). Introduction PCPs have gained popularity in recent years and, thus, have increased their footprint within the operator’s assets. At the time of writing, PCP wells contribute 19% of the operator’s net oil production, with a minimal water-cut rate per well in comparison with all other artificial-lift wells. The number of PCPs has almost doubled since the inception of an exception-based-surveillance (EBS) system in 2015, and the effort in configuring and managing EBS alerts had become more challenging, with each engineer handling an average of 30 EBS alerts per week. In 2018, the operator’s PCP team completed a Lean project for sustainable PCP well modeling by automating the complete process in the WMS (a nodal-analysis-based real-time application) and delivering 100% real-time models for all active PCP wells. This was achieved by building and integrating the operator’s corporate database for PCP wells with the WMS. The system was developed for performing PCP well modeling by collecting well information automatically from various corporate databases such as an artificial-lift database, a subsurface database, a production database, and reservoir and pressure/volume/temperature databases, among others (Fig. 1).