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Open AccessArticle

Static Geological Modelling with Knowledge Driven Methodology

1
State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan 430071, China
2
Dimue Technology, Ltd. Co., Wuhan 430000, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(19), 3802; https://doi.org/10.3390/en12193802
Received: 20 August 2019 / Revised: 2 October 2019 / Accepted: 6 October 2019 / Published: 8 October 2019
(This article belongs to the Section Geo-Energy)
Geological modelling is an important topic of oil and gas exploration and production. A new knowledge driven methodology of geological modelling is proposed to address the problem of “hard data” limitation and modelling efficiency of the conventional data driven methodology. Accordingly, a new geological modelling software (DMatlas) (V1.0, Dimue, Wuhan, China) has been developed adopting a grid-free, object-based methodology. Conceptual facies models can be created for various depositional environments (such as fluvial, delta and carbonates). The models can be built largely based on geologists’ understandings with “soft data” such as outcrops analysis and geological maps from public literatures. Basic structures (fault, folds, and discrete fracture network) can be easily constructed according to their main features. In this methodology, models can be shared and re-used by other modelers or projects. Large number of model templates help to improve the modelling work efficiency. To demonstrate the tool, two case studies of geological modelling with knowledge driven methodology are introduced: (1) Suizhong 36-1 field which is a delta depositional environment in Bohai basin, China; (2) a site of the north Oman fracture system. The case studies show the efficiency and reliability within the new methodology. View Full-Text
Keywords: geological modelling; knowledge-driven methodology; depositional environments; structure; oil and gas exploration and production geological modelling; knowledge-driven methodology; depositional environments; structure; oil and gas exploration and production
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MDPI and ACS Style

Li, J.; Zhang, X.; Lu, B.; Ahmed, R.; Zhang, Q. Static Geological Modelling with Knowledge Driven Methodology. Energies 2019, 12, 3802.

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