ESP "Smart Flow" Integrates Quality and Control Data for Diagnostics and Optimization in Real Time (Part of KwIDF Project)

Al-Jasmi, Ahmad; Nasr, Hatem N.; Goel, H. K.; Moricca, Giuseppe; Carvajal, Gustavo; Dhar, J.; Querales, M.; Villamizar, M.; Cullick, A.S.; Rodríguez, José Antonio Alonso; Velasquez, Guillermo; Zhai, Yikui; Bermúdez, Fátima; Khain, J.

doi:10.2118/167394-ms

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…e comprehensive parameter diagnosis method uses artificial intelligence algorithms to analyze multiple real-time monitoring parameters and obtain the diagnosis results. For example, Al-Jasmi et al and Bermudez et al [12,13] established fault diagnosis models for ESP wells based on fuzzy logic algorithms, fault trend tables, and weighting factors. ey realized the diagnosis of five types of faults for ESP wells.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis Method and Application of ESP Well Based on SPC Rules and Real-Time Data Fusion

Yang

Wang

Zheng³

et al. 2022

Mathematical Problems in Engineering

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Aiming at the popularization and application of a real-time monitoring parameter acquisition system of the electric submersible pump (ESP) well, this paper proposes a fault diagnosis method of ESP well operation based on the SPC rule and prior knowledge fusion. Based on the study of parameter variation rules of ESP well, the SPC expansion rule model is established; by analyzing the variation of some typical characteristic parameters of ESP well, combined with SPC expansion rules and expert experience, a priori knowledge of fault diagnosis of ESP well is formed, that is, multiparameter fault analysis table and weight factor; the SPC extended rule model and prior knowledge are fused to establish the fault probability model of ESP well, form the fault diagnosis method of ESP well, develop the online fault diagnosis software of ESP well, and deploy it in 425 ESP wells in a block. Taking five types of tubing leakage, pump wear, shaft breakage, gas influence, and pump plugging as examples, the application process of fault diagnosis method is analyzed. The research and application show that compared with other fault diagnosis methods, this method needs a smaller time window and higher diagnosis accuracy. By setting multiple time windows, this diagnosis method is applied to calculate the fault probability of ESP well in real time, solve the real time and accurate identification of 14 sudden faults and gradual faults, and significantly improve the intelligent diagnosis level of production faults of ESP well.

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Section: Introductionmentioning

confidence: 99%

Fault Diagnosis Method and Application of ESP Well Based on SPC Rules and Real-Time Data Fusion

Yang

Wang

Zheng³

et al. 2022

Mathematical Problems in Engineering

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“…The complexity of operating ESP-lifted fields is shown in [10], where improving and automating the workflow for production operations to improve the asset performance, including optimization and diagnostics based on real-time data, is discussed. In [11], optimization of ESP-lifted oil fields based on steady-state optimization and simple PI-control is considered.…”

Section: Introductionmentioning

confidence: 99%

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Binder

Kufoalor

Pavlov

et al. 2014

2014 IEEE Conference on Control Applications (CCA)

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Abstract-Electric Submersible Pumps (ESP) can be installed in oil wells to create artificial lift, in order to increase recovery from the reservoir, and boost the production rate. A Model Predictive Controller (MPC) for an ESP, based on linearized models, is developed and designed using SEPTIC (Statoil's in-house software tool for MPC), and implemented on a Programmable Logic Controller (PLC). Automatic code generators have been utilized to generate an applicationspecific MPC controller in ANSI C code. Hardware-in-the-loop simulation results show that the control performance of the PLC implementation is comparable to the original SEPTIC controller.

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Intelligent Digital Oilfield Implementation: A Case Study of Change Management Strategies to Ensure Success

Al-Jasmi

Goel

Cerda

et al. 2013

Day 3 Wed, October 30, 2013

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The successful implementation of a world-leading integrated digital oilfield (IDOF) with a national oil company (NOC) required extremely careful and innovative management of the large-scale change required for the project. In particular, the "people side" of that change management was key for embedding the project in the NOC organization and, in turn, making the USD multi-million project a success.This paper outlines the NOC expectations and describes the steps and processes required to initiate and mobilize the people side of change in the IDOF project and also details the change management challenges experienced before the peopleside-focused strategy was determined to be the way forward. Using a simple people-side-focused change methodology not only ensured that the project was successful in terms of return on capital employed (ROCE) but also began the process of ownership and eased the adoption of the IDOF into the current NOC organization. The change management methodology described in this paper was designed to cover and mitigate important challenges that were relevant in driving the people side of change, particularly the following:• WIIFM-"what's in it for me" scenarios.• Culture-the way things are done around here.• Success-collaboration, technology leap frogging, people, and oil gains.This paper describes the main successes, key lessons learned, observations, and progress made against the clearly defined NOC expectations. VisionThe IDOF project was initially created as a visionary state-of-the-art prototype pilot for the NOC. From the outset of the project, expectations were at a very high level, both in terms of the technology that was envisioned to be used for oil production optimization and the caliber of people involved in the IDOF.This IDOF is seen as a technological game changer, one of the NOC's most strategically important projects in terms of optimizing oil production. In the IDOF collaborative work environment (CWE), a suite of advanced smartflow workflows provide smart functionalities, coupling geological and reservoir subsurface models with production operation workflows. The workflows monitor real-time data to help improve well performance, reduce well downtime, and increase field performance.The NOC executives and the leadership of the management in the research and technology (R&T) department were clear in their vision and aspirations-this project should lead not only the oil and gas Gulf Cooperation Council (GCC) countries but also in the field of IDOF concepts and technology worldwide. In addition, it should position the NOC as the preeminent world leader in IDOF technology. The internal design concepts for the new collaboration center (Fig. 1) were also fully maximized to match the NOC's expectations. This helped to deliver one of the most elaborate and comfortable workplaces within the oil and gas sector. The combination of a clear vision and high expectations whilst working in partnership with a major oil service organization immediately attracted the best technology talent in the fie...

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ESP "Smart Flow" Integrates Quality and Control Data for Diagnostics and Optimization in Real Time (Part of KwIDF Project)

Cited by 4 publications

References 9 publications

Fault Diagnosis Method and Application of ESP Well Based on SPC Rules and Real-Time Data Fusion

Fault Diagnosis Method and Application of ESP Well Based on SPC Rules and Real-Time Data Fusion

Embedded Model Predictive Control for an Electric Submersible Pump on a Programmable Logic Controller

Intelligent Digital Oilfield Implementation: A Case Study of Change Management Strategies to Ensure Success

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