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.
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.