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Rod-Pump Optimization: Big Data Helps Accelerate and Improve Operations

Topics: Artificial lift

This paper presents how a US onshore operator took a three-step approach to optimize more than 100 rod-pump wells. The approach involved data consolidation, automated work flows, and interactive data visualization. This approach led to increased unit run times, decreased unit cycling, improved production and equipment surveillance, and increased staff productivity. The ultimate goal was to increase profitability by decreasing lifting costs and increasing operating efficiency.

Introduction

The processes and tools described in this paper cover a subset of approximately 125 wells in eastern Montana and western North Dakota, but they have been designed to be applicable and scalable to any fields that use rod-pump artificial-lift systems with supervisory control and data acquisition (SCADA). Simple modifications can be made to the tools and processes for wells that do not have SCADA capabilities.

While optimization efforts and best practices have been implemented for the subject rod-pump systems during the past 6 decades, many opportunities remain to create additional value. Empirical knowledge from field personnel serves as the basis for the analytical model. Categorizing and quantifying the observations made by the field personnel is critical to developing any analytical model involving oil and gas operations. On the basis of feedback from field personnel and engineers, the following areas had the most potential for improvement: data consolidation, automated work flows, and data visualization.

The data-consolidation issue stems from data being located in multiple file locations, sometimes being stored in nontabular formats and initially lacking the necessary unique identifiers for mapping between databases. Automated work flows were essentially nonexistent; wells were analyzed individually using deterministic, static data. Data were previously visualized in multiple locations but never integrated into a single, interactive visualization tool.

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 181216, “Proactive Rod-Pump Optimization: Leveraging Big Data To Accelerate and Improve Operations,” by Tyler Palmer, SPE, and Mark Turland, SPE, Denbury Resources, prepared for the 2016 SPE North American Artificial Lift Conference and Exhibition, The Woodlands, Texas, USA, 25–27 October. The paper has not been peer reviewed.
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Rod-Pump Optimization: Big Data Helps Accelerate and Improve Operations

01 July 2018

Volume: 70 | Issue: 7

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