This paper describes a new method to continuously monitor and diagnose the condition of wells producing via continuous gas lift. The paper describes the application of this system in a mature onshore gas lift field in the Western United States and the results obtained therein. A central problem related to the operation of gas lift wells is the ability to identify underperforming wells and to address the underlying issues appropriately and in a timely manner. This problem is compounded by the trend toward leaner operations and relative scarcity of application specific domain knowledge. The purpose of this method is to address these issues by leveraging real time data, gas lift domain expertise and proven steady state analysis techniques in a desktop software application. This system performs four key functions: monitoring the wells' condition by collecting data; assessing the meaning of this data; recommending actions for correcting problems and responding to threats; and explaining their recommendations. The performance of the system has met initial expectations and provided additional unforeseen benefits. This paper sites specific cases which compare agent predictions to expert diagnoses and quantify the benefits of taking the recommended actions. What was found was that while the correct diagnoses of well performance issues was beneficial, the real benefit was in allowing production engineers to analyze a greater number of wells in far less time. To that end, the paper will discuss the role of this system as it relates to the overall production management workflow. The success of this project has demonstrated that intelligent agents can be used to effectively perform functions which were historically performed by a handful of experts. The paper will discuss key system design features which enable this level of functionality as well as other potential areas where the technology can be extended in the future. Introduction One of the current challenges facing the upstream E&P industry is the growing scarcity of specialist domain expertise and trained personnel needed to efficiently operate oil and gas assets. In cases where these resources are limited or unavailable, automation technology has often been touted as a solution. While the introduction of such technology has delivered numerous improvements in operational efficiency, it has also introduced new challenges. One such challenge involves the introduction of vast quantities of data that results in minimal actionable information 1,2. Operators are faced not only with the information technology task of managing this data, but also with the business challenge of leveraging the data to improve their profitability. In response to this new challenge, a growing number of projects are being initiated to help close this gap between data and information. This paper discusses one such effort. In this project, new technology has been developed to assist production engineers in the well-by-well optimization of gas lift systems. Well-by-well optimization has long been recognized as having value 3, but has often proven impractical to carry out on a routine basis due to the labor-intensive nature of the work and the limited number of individuals with the required level of expertise to perform it. This project sought to solve this problem by developing a system of intelligent agents which leverage both real time data and gas lift domain knowledge to assist engineers in these well-by-well optimization tasks.

Авторское право 2008 г., Общество инженеров-нефтяников Этот доклад был приготавливан предьявления в 2008 Российской нефтьегазовой технической конференции и выставке состоится в Москве 28-30 октабря 2008.Данный доклад был выбран для проведения презентации Программным комитетом SPE по результатам экспертизы информации, содержащейся в представленном авторами резюме. Экспертиза содержания доклада Обществом инженеров-нефтяников не выполнялась, и доклад подлежит внесению исправлений и корректировок авторами. Материал в том виде, в котором он представлен, не обязательно отражает точку зрения Общества инженеров-нефтяников, его должностных лиц или участников. Доклады, представленные на конференциях SPE, подлежат экспертизе со стороны Редакционных Комитетов Общества инженеров-нефтяников. Электронное копирование, распространение или хранение любой части данного доклада в коммерческих целях без предварительного письменного согласия Общества инженеров-нефтяников запрещается. Разрешение на воспроизведение в печатном виде распространяется только на резюме длиной не более 300 слов; при этом копировать иллюстрации не разрешается. Резюме должно содержать явно выраженную ссылку на то, где и кем был представлен данный доклад. Write Librarian, SPE, P.O.Box 833836, Richardson, TX 75083-3836 U.S.A., факс 01-972-952-9435.

A major exploration and production company operated Block 15 and unified fields Eden-Yuturi and Limoncocha from 1986 to May 2006, when the contract passed back to the Ecuadorian Government. In 2004 a decision was made to implement an ESP Real Time Monitoring and Diagnosis system in order to optimize production and improve ESP operations. The system includes automation hardware equipment and a server-client software package. The purpose of this paper is to give details about the benefits of remote monitoring and control of Electrical Submersible Pumps, and the real results achieved from using the ESP monitoring and diagnosis system to monitor, analyze, and remotely control ESP performance at Block 15. In this paper, we will highlight ways in which the ESP diagnosis system has enabled material improvements in operational efficiency at Block 15.

This paper describes a new method to continuously monitor and diagnose the condition of wells producing via continuous gas lift. The paper describes the application of this system in a mature onshore gas lift field in the Western United States and the results obtained therein. A central problem related to the operation of gas lift wells is the ability to identify underperforming wells and to address the underlying issues appropriately and in a timely manner. This problem is compounded by the trend toward leaner operations and relative scarcity of application specific domain knowledge. The purpose of this method is to address these issues by leveraging real time data, gas lift domain expertise and proven steady state analysis techniques in a desktop software application.This system performs four key functions: monitoring the wells' condition by collecting data; assessing the meaning of this data; recommending actions for correcting problems and responding to threats; and explaining their recommendations.The performance of the system has met initial expectations and provided additional unforeseen benefits. This paper sites specific cases which compare agent predictions to expert diagnoses and quantify the benefits of taking the recommended actions. What was found was that while the correct diagnoses of well performance issues was beneficial, the real benefit was in allowing production engineers to analyze a greater number of wells in far less time. To that end, the paper will discuss the role of this system as it relates to the overall production management workflow.The success of this project has demonstrated that intelligent agents can be used to effectively perform functions which were historically performed by a handful of experts. The paper will discuss key system design features which enable this level of functionality as well as other potential areas where the technology can be extended in the future.

Historically, the electric-submersible-pump (ESP) system has been the most cost-effective artificial-lift technology to draw down deep wells with flow rates of more than 200 STB/D. In lower-rate wells, other technologies such as rod pump systems have proven to be more cost effective. However, in recent years the long-stroke pumping unit has extended the rod-lift operating envelope to the point that rod lift now provides competitively effective pumping in wells traditionally using ESPs. The case study within this paper focuses on a mature well located in a Petrobell's field in South America, Cachiyacu 1, in which a production decline rendered the existing ESP system oversized for the well conditions. The operator was seeking a more efficient lift solution before ESP failure due to down-thrust operation. A comparison of energy consumption, efficiencies, and operating expenses (OPEX) was used to evaluate the two artificial-lift options—a smaller ESP system or a long-stroke pumping unit. This study compares the costs of power and workovers between an ESP and a long-stroke pumping unit. It shows that over a well-documented period of time, the long-stroke pumping unit reduces power consumption by providing greater operational efficiency than ESPs at similar depths and rates. The long-stoke pumping unit also reduces workover costs with less expensive downhole components. This operator realized significant financial savings and reduced energy usage by choosing the long-stroke pumping unit. Although both the ESP system and the long-stroke pumping unit can deliver similar production rates, in this case, the long-stroke pumping unit was able to provide a higher production rate than the ESP. The LSPU also provided a more cost effective option in this application (CAPEX & OPEX).