Unconventional/complex reservoirs

AI, Data Analytics Enable Approach to History Matching in Geologically Complex Field

This paper outlines an approach to history matching that uses artificial intelligence with an artificial neural network and data-driven analytics. The approach has been used to mitigate history-matching challenges in a mature, highly geologically complex field offshore Malaysia.

Depiction of reservoir zones of Field “A”.
Depiction of reservoir zones of Field “A”.
SPE 202460

History matching is a critical step for dynamic reservoir modeling to establish a reliable, predictive model. Numerous approaches have emerged over decades to accomplish a robust history-matched reservoir model. As geological and completion complexity of oil and gas fields increase, building a fully representative predictive reservoir model can be arduous to almost impossible. The complete paper outlines an approach to history matching that uses artificial intelligence (AI) with an artificial neural network (ANN) and data-driven analytics.

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