Natural decline in various mainstream oilfield reserves and the high investment capital in upstream exploration and project development have promoted attention towards smaller oilfields referred to as Marginal fields....Natural decline in various mainstream oilfield reserves and the high investment capital in upstream exploration and project development have promoted attention towards smaller oilfields referred to as Marginal fields. This provides operators the opportunity to commence exploration and production with minimum requirements of design, installation, and operations. Although the low Capital Expenditure (CAPEX) requirement favors the start-up of marginal oilfield operations, several operators are not able to sustain the field’s operations due to the high Operational Expenditure (OPEX), particularly arising from facilities’ maintenance. The aim of this paper is to review the maintenance strategies adopted in marginal oilfields, assess their effectiveness, and provide a pointer towards efficient and viable maintenance strategies for the sustainability of marginal oilfields. The study showed that time-based preventive maintenance is predominant in the oil industry, which constitutes up to 40% of net operational expenses. In other cases, reactive maintenance is adopted, which often results in an unplanned shutdown, known to be responsible for nearly half of the overall losses of an oil facility. A paradigm shift in maintenance to Reliability Centered Maintenance (RCM) was explored for marginal oilfield, with a comprehensive review of various maintenance strategies, ranging from maintenance optimization strategies, Heuristics and Metaheuristics, Artificial Intelligence (AI), and Data Mining techniques. It was observed that the application of AI best addresses the proposed RCM for marginal oilfields. This was drawn from the recorded limitations of the other concepts from verifiable similar works, where different AI techniques and Data analytics methods have been successfully applied to aid RCM.展开更多
With the development of oilfield exploration and mining, the research on continental oil and gas reservoirs has been gradually refined, and the exploration target of offshore reservoir has also entered the hot studyst...With the development of oilfield exploration and mining, the research on continental oil and gas reservoirs has been gradually refined, and the exploration target of offshore reservoir has also entered the hot studystage of small sand bodies, small fault blocks, complex structures, low permeability and various heterogeneous geological bodies. Thus, the marine oil and gas development will inevitably enter thecomplicated reservoir stage;meanwhile the corresponding assessment technologies, engineering measures andexploration method should be designed delicately. Studying on hydraulic flow unit of low permeability reservoir of offshore oilfield has practical significance for connectivity degree and remaining oil distribution. An integrated method which contains the data mining and flow unit identification part was used on the flow unit prediction of low permeability reservoir;the predicted results?were compared with mature commercial system results for verifying its application. This strategy is successfully applied to increase the accuracy by choosing the outstanding prediction result. Excellent computing system could provide more accurate geological information for reservoir characterization.展开更多
Reservoir connectivity is a critical issue in the process of oil-gas exploration and development. According to the theory of fluid mechanics and the achievements of many scholars, a connected reservoir coincides with ...Reservoir connectivity is a critical issue in the process of oil-gas exploration and development. According to the theory of fluid mechanics and the achievements of many scholars, a connected reservoir coincides with a unified formation pressure system;there is a linear relationship between formation pressure and depth in normal pressure system reservoir. However, in high-permeability or multi-phase fluid reservoirs, this method has poor applicability and limitations. Through theoretical analysis and formula derivation, a new method for judging the connectivity of normal pressure reservoirs is found, that is, the inverse proportional function relationship between the pressure coefficient and the depth. In this paper, the relationship between the pressure system and the inverse proportional function has been verified. The function of the same pressure system is unique, monotonic, and has unified asymptote and symmetry axis and vice versa. Examples show that the inverse proportional function is more accurate and reliable for judging reservoir connectivity than the linear function.展开更多
文摘Natural decline in various mainstream oilfield reserves and the high investment capital in upstream exploration and project development have promoted attention towards smaller oilfields referred to as Marginal fields. This provides operators the opportunity to commence exploration and production with minimum requirements of design, installation, and operations. Although the low Capital Expenditure (CAPEX) requirement favors the start-up of marginal oilfield operations, several operators are not able to sustain the field’s operations due to the high Operational Expenditure (OPEX), particularly arising from facilities’ maintenance. The aim of this paper is to review the maintenance strategies adopted in marginal oilfields, assess their effectiveness, and provide a pointer towards efficient and viable maintenance strategies for the sustainability of marginal oilfields. The study showed that time-based preventive maintenance is predominant in the oil industry, which constitutes up to 40% of net operational expenses. In other cases, reactive maintenance is adopted, which often results in an unplanned shutdown, known to be responsible for nearly half of the overall losses of an oil facility. A paradigm shift in maintenance to Reliability Centered Maintenance (RCM) was explored for marginal oilfield, with a comprehensive review of various maintenance strategies, ranging from maintenance optimization strategies, Heuristics and Metaheuristics, Artificial Intelligence (AI), and Data Mining techniques. It was observed that the application of AI best addresses the proposed RCM for marginal oilfields. This was drawn from the recorded limitations of the other concepts from verifiable similar works, where different AI techniques and Data analytics methods have been successfully applied to aid RCM.
文摘With the development of oilfield exploration and mining, the research on continental oil and gas reservoirs has been gradually refined, and the exploration target of offshore reservoir has also entered the hot studystage of small sand bodies, small fault blocks, complex structures, low permeability and various heterogeneous geological bodies. Thus, the marine oil and gas development will inevitably enter thecomplicated reservoir stage;meanwhile the corresponding assessment technologies, engineering measures andexploration method should be designed delicately. Studying on hydraulic flow unit of low permeability reservoir of offshore oilfield has practical significance for connectivity degree and remaining oil distribution. An integrated method which contains the data mining and flow unit identification part was used on the flow unit prediction of low permeability reservoir;the predicted results?were compared with mature commercial system results for verifying its application. This strategy is successfully applied to increase the accuracy by choosing the outstanding prediction result. Excellent computing system could provide more accurate geological information for reservoir characterization.
文摘Reservoir connectivity is a critical issue in the process of oil-gas exploration and development. According to the theory of fluid mechanics and the achievements of many scholars, a connected reservoir coincides with a unified formation pressure system;there is a linear relationship between formation pressure and depth in normal pressure system reservoir. However, in high-permeability or multi-phase fluid reservoirs, this method has poor applicability and limitations. Through theoretical analysis and formula derivation, a new method for judging the connectivity of normal pressure reservoirs is found, that is, the inverse proportional function relationship between the pressure coefficient and the depth. In this paper, the relationship between the pressure system and the inverse proportional function has been verified. The function of the same pressure system is unique, monotonic, and has unified asymptote and symmetry axis and vice versa. Examples show that the inverse proportional function is more accurate and reliable for judging reservoir connectivity than the linear function.
