Real Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study

Stephenson, Gregory B.; Molotkov, Roman; Guzman, Neil de; Lafferty, Larry

doi:10.2118/124926-ms

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…In contrast to neural networks, associative memories are "white boxes"-they can be configured to explain their decisions. Stephenson et al (2010) describe the use of an associative memory for gas lift well diagnosis. The machine-learning processes in intelligent agents entail human-directed "machine learning."…”

Section: Aipa State-of-the-art Reviewmentioning

confidence: 99%

State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

Bravo

Saputelli²,

Rivas³

et al. 2013

SPE Journal

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Artificial intelligence (AI) has been used for more than 2 decades as a development tool for solutions in several areas of the exploration and production (E&P) industry: virtual sensing, production control and optimization, forecasting, and simulation, among many others. Nevertheless, AI applications have not been consolidated as standard solutions in the industry, and most common applications of AI still are case studies and pilot projects.In this work, an analysis of a survey conducted on a broad group of professionals related to several E&P operations and service companies is presented. This survey captures the level of AI knowledge in the industry, the most common application areas, and the expectations of the users from AI-based solutions. It also includes a literature review of technical papers related to AI applications and trends in the market and in research and development.The survey helped to verify that (a) data mining and neural networks are by far the most popular AI technologies used in the industry; (b) approximately 50% of respondents declared they were somehow engaged in applying workflow automation, automatic process control, rule-based case reasoning, data mining, proxy models, and virtual environments; (c) production is the area most affected by the applications of AI technologies; (d) the perceived level of available literature and public knowledge of AI technologies is generally low; and (e) although availability of information is generally low, it is not perceived equally among different roles.This work aims to be a guide for personnel responsible for production and asset management on how AI-based applications can add more value and improve their decision making. The results of the survey offer a guideline on which tools to consider for each particular oil and gas challenge. It also illustrates how AI techniques will play an important role in future developments of information-technology (IT) solutions in the E&P industry. IntroductionAlthough there is hardly a rigorous definition of the term "artificial intelligence" that is unequivocally accepted, the tools of AI and its intended uses have been well studied for decades and many applications have appeared. Loosely speaking, AI is the capability of machines (usually in the form of computer hardware and software) to mimic or exceed human intelligence in everyday engineering and scientific tasks associated with perceiving, reasoning, and acting. Because human intelligence is multifaceted, so is AI, comprising goals that range from knowledge representation and reasoning to learning, visual perception, and language understanding (Winston 1992). AI techniques have been present in the E&P industry for many years. A quick literature search reveals application of AI in SPE scientific and engineering papers as early as in the 1970s. There are numerous references about the

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Section: Aipa State-of-the-art Reviewmentioning

confidence: 99%

State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

Bravo

Saputelli²,

Rivas³

et al. 2013

SPE Journal

View full text Add to dashboard Cite

show abstract

“…(Olijnik et al, 1996, Anderson, 2005, Vachon and Furui, 2005, Ali and Shafiq, 2008, Ansah et al, 2009, Soegiyono et al, 2010, Al-Mohanna et al, 2011. Related procedures and equipment are available for gas lifted wells with I-completions (Cedeno and Ortiz, 2007, Vasper, 2008, Iyamu et al, 2008, Stephenson et al, 2010. (Konopczynski et al, 2002) describe how an ICV reduces the water cut and the liquid production while increasing the oil production rate.…”

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confidence: 99%

Role of Artificial Lift in Wells With a Downhole, Flow Control Completion

Gasbarri

Muradov²,

Davies³

2013

SPE Offshore Europe Oil and Gas Conference and Exhibition

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Several hundred of Intelligent wells well that combine downhole flow control and monitoring have been installed over the last decade in a wide range of reservoir production scenarios. Numerous publications have reported the successful use of the technology to reduce the number of well interventions, improve sweep efficiency, reduce risk, mitigate production problems, etc. A number of zonal inflow and outflow control methodologies have been proposed to meet a wide range of different well objectives as well as different production or injection conditions. Research still continues in the areas of simple reactive or predefined passive control methods employed by Intelligent wells. This is even more true if it is planned to use proactive control which requires optimisation of a complex multivariable problem.Efficient downhole flow control comes at the cost of adding an additional pressure loss. Such losses can be significant, jeopardizing the well productivity and sometimes carrying the risk of a reduced well performance of the intelligent well when compared to the corresponding conventional well. Installing artificial lift can compensate for this reduced well performance; not only extending the well life, but also adding additional well control flexibility. However, it also poses two extra problems: how to (a) optimally design the artificial lift equipment and (b) avoid interference between the I-well's control of the zonal inflow and control of the artificial lift.This paper sets out how to(1) Add control flexibility to downhole flow control by artificial lift and (2) Design an electric submersible pump that operates flexibly with down hole, multi-zone inflow control actions.Improved active and passive downhole flow control will be discussed in a rigorous, mathematical manner that allows the conclusion that the combination of artificial lift and downhole flow control provides greater zonal flow control flexibility and reduces the inflow imbalance. Also, two conceptual, electric submersible pump design options, employing (1) a variable wellhead choke and (2) a variable pump operating frequency, are proposed and illustrated. Both of these proposed pump design options could cope with the changing well inflow performance created by downhole flow control devices in situations where the standard pump design workflow was ineffective.

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Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study

Stephenson

Molotkov

Guzman³

et al. 2010

SPE Production &Amp; Operations

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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.

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Real Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study

Cited by 3 publications

References 20 publications

State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

State of the Art of Artificial Intelligence and Predictive Analytics in the E&P Industry: A Technology Survey

Role of Artificial Lift in Wells With a Downhole, Flow Control Completion

Real-Time Diagnostics of Gas Lift Systems Using Intelligent Agents: A Case Study

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