In the field of 3 D geologic modeling, researchers often pay more attention to modeling methods and workflows, but neglect the quantitative evaluation of models. If the evaluation is narrowed to the same reservoir typ...In the field of 3 D geologic modeling, researchers often pay more attention to modeling methods and workflows, but neglect the quantitative evaluation of models. If the evaluation is narrowed to the same reservoir type, the comparability and practicality of quantitative assessment will be emerging. The evaluation system should include three parts: data verification, geological understanding and process check. Data verification mainly involves testing the accuracy of local prediction with actual data, and geological understanding is to examine whether the global estimation honors geological principles and prior insights. Process check is also indispensable to avoid occasionality. To this end, we produced a set of assessment criteria, taking complex fault-block sandstone oil reservoir as an example. To be specific, thirteen characteristic parameters were totally selected, setting weights according to their rated importance, formulating three-level evaluation standards in a centesimal system for each characteristic parameter, and obtaining the final assessment based on the cumulative score. The results indicate that such evaluation can not only access the quality of the model objectively and comprehensively, but also identify the aspects in need of improvement through the deduction items.展开更多
基金Supported by the Sinopec Science and Technology Major Project(G5800-17-ZS-KJB009)
文摘In the field of 3 D geologic modeling, researchers often pay more attention to modeling methods and workflows, but neglect the quantitative evaluation of models. If the evaluation is narrowed to the same reservoir type, the comparability and practicality of quantitative assessment will be emerging. The evaluation system should include three parts: data verification, geological understanding and process check. Data verification mainly involves testing the accuracy of local prediction with actual data, and geological understanding is to examine whether the global estimation honors geological principles and prior insights. Process check is also indispensable to avoid occasionality. To this end, we produced a set of assessment criteria, taking complex fault-block sandstone oil reservoir as an example. To be specific, thirteen characteristic parameters were totally selected, setting weights according to their rated importance, formulating three-level evaluation standards in a centesimal system for each characteristic parameter, and obtaining the final assessment based on the cumulative score. The results indicate that such evaluation can not only access the quality of the model objectively and comprehensively, but also identify the aspects in need of improvement through the deduction items.
