“…Remark 1: Many commentators are forecasting a terminal decline in the production of conventional oil [54]. What is worse, due to the continuous decrease in production rates of SRPS, the number of installations of SRPS in extreme environments is increasing [55]. By introducing digital workers to parallel oil fields, the number of human workers in tough areas is dramatically reduced, thus, lessening economic inputs and ensuring the safety of human workers.…”
Section: A Framework Of Metaverses-based Parallel Oil Fieldsmentioning
Aiming to provide a novel paradigm of oil fields, metaverses-based parallel oil fields are proposed in this article. Compared with the existing smart/intelligent oil fields in cyber-physical systems (CPS), parallel oil fields can take human factors into full consideration and expand the operation space to cyber-physical-social systems (CPSS), which can be regarded as the abstract and scientific explanation of metaverses. In the proposed parallel oil fields, there are three kinds of workers (human workers, digital workers, and robotic workers) coordinating to construct a more reliable and intelligent oil field. Furthermore, the framework and methodology of parallel oil fields are illustrated by parallel systems and the artificial systems, computational experiments, and parallel executions (ACP) approach. Based on the proposed framework, parallel oil fields are capable of generating a more trustworthy artificial system and guaranteeing the realization of the 6S (safety, security, sustainability, sensitivity, service, and smartness) goal. Finally, based on dynamometer cards, fault diagnosis of sucker rod pumping systems (SRPS) is investigated in parallel oil fields.
“…Remark 1: Many commentators are forecasting a terminal decline in the production of conventional oil [54]. What is worse, due to the continuous decrease in production rates of SRPS, the number of installations of SRPS in extreme environments is increasing [55]. By introducing digital workers to parallel oil fields, the number of human workers in tough areas is dramatically reduced, thus, lessening economic inputs and ensuring the safety of human workers.…”
Section: A Framework Of Metaverses-based Parallel Oil Fieldsmentioning
Aiming to provide a novel paradigm of oil fields, metaverses-based parallel oil fields are proposed in this article. Compared with the existing smart/intelligent oil fields in cyber-physical systems (CPS), parallel oil fields can take human factors into full consideration and expand the operation space to cyber-physical-social systems (CPSS), which can be regarded as the abstract and scientific explanation of metaverses. In the proposed parallel oil fields, there are three kinds of workers (human workers, digital workers, and robotic workers) coordinating to construct a more reliable and intelligent oil field. Furthermore, the framework and methodology of parallel oil fields are illustrated by parallel systems and the artificial systems, computational experiments, and parallel executions (ACP) approach. Based on the proposed framework, parallel oil fields are capable of generating a more trustworthy artificial system and guaranteeing the realization of the 6S (safety, security, sustainability, sensitivity, service, and smartness) goal. Finally, based on dynamometer cards, fault diagnosis of sucker rod pumping systems (SRPS) is investigated in parallel oil fields.
“…The relationship between the polished rod position and the crank angle θ is as follows: In both modeling and indirect measurement (inference) of the polished rod load, relevant publications can be found in recent technical literature [1], [7]- [9]. In the context of mathematical modeling, a dynamic description of pumping dynamics that accounts for system inertia was proposed in [10], as follows:…”
Rod pumping systems typically require the analysis of dynamometer cards for fault diagnosis. While external instrumentation assists in obtaining these cards, it simultaneously raises monitoring costs and complexity. To address this issue, this paper introduces a parameter estimator that integrates the equivalent circuit model of an induction motor with the beam pumping unit model. We have compared the performance of two practical estimators, utilizing the terminal quantities of the driving motor as inputs. The results demonstrate surface dynamometer cards under varying operational conditions of the oil well. By augmenting the estimator's input variables, the estimated cards align more closely with the actual ones. This practical application proposes an alternative method for acquiring the surface dynamometer card, which can function as a supplementary approach in fault diagnostics and contribute to informed maintenance decisions for the pumping unit.
“…Researchers have extensively investigated the problem of pumping well fault diagnosis using two main approaches. The first is the method based on theoretical analysis [ 3 ], which involves establishing the operating principles and corresponding mathematical models of the sucker rod pumping system, followed by the simulation calculation of various pumping well fault types. However, given the complexity of the rod pumping system and the interactions among various fluids in the wellbore, this method has limited applications.…”
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