A Novel Digital Approach to Predict Production Rates from PCP Wells

Abstract

Progressive cavity pumps (PCP) have been used as artificial lift system for heavy oil lifting, low productivity wells and other challenging conditions which are common characteristics of brownfields. In addition to those conditions, there is the current complicated economic environment in which operating companies seek to reduce investments while enhancing field production operations with low-cost solutions aiming to increase the overall's field recovery factor. The initial step when trying to enhance field production operations in wells operating with PCPs as artificial lift system is performing a well-level analysis. During this analysis, the existing operational conditions and its corresponding production are evaluated. The continuity and accuracy of this analysis is highly dependent on the data input for analysis purposes. For instance, the rate of production is required as input and due to the nature of operation in brownfields, this value is not measured with the required frequency needed for performing a proper production enhancement analysis. This paper aims to provide a simple, automated, and accurate way to perform a calculated rate of production that is cost effective and easy to maintain, capable of being used during field production operations enhancement analysis, and applicable to wells operating with PCPs as artificial lift in heavy oil conditions, using regression and analytical methods. Both methods are being used part of a digital oilfield solution implemented in a heavy oil brownfield with telemetry-instrumented PCP wells. This solution is working inside a production operations platform that validates input data, manages different frequencies and types of data, and automatically calculates a production rate, which is then pushed to a visualization dashboard. Results provide an accurate production rate estimate suitable for reservoir engineering analyses while providing insight for the production operations enhancement.