Physics-Guided Data-Driven Workflow Identifies Bypassed Oil and Optimizes Infill
Authors: Carpenter Chris 
Published: January 2025

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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 218429, “Bypassed Oil Identification and Infill Optimization by a Physics-Guided Data-Driven Workflow: A North Sea Case Study,” by Babak Moradi, SPE, and Susan Behjat, Three60 Energy, and Sándor Völgyi, Wintershall Dea, et al. The paper has not been peer reviewed.

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The complete paper focuses on the vital task of identifying bypassed oil and locating the remaining oil in mature fields, emphasizing the significance of these activities in sustaining efficient oilfield exploitation. The paper introduces a novel digital hybrid workflow, guided by physics principles and driven by data, that is further enhanced by the integration of 4D time-lapse data.

Subject Field X
In brownfields, the presence of a considerable number of wells, multiple surveillance measurements, and extensive historical production data present unique opportunities for the application of data-driven techniques. This study used a hybrid approach, physics-informed and data-driven, to expedite the process of mapping the remaining oil, reducing the timeline from months to weeks.
Field X was discovered in 2007 on the Utsira High in the Norwegian sector of the North Sea. First oil was produced from the field in November 2015. The field was deposited in a continental half-graben setting. Reservoir quality varies from moderate to very good in marine and aeolian sandstone, while the quality is poorer in alluvial sandstone and conglomerate. Oil also is proven in the underlying basement. The reservoir is at a depth of 1900 m. The field is produced by pressure support from water injection. At the time, the field consisted of 13 production wells and four injection wells. One of the wells was converted from a producer to an injector in 2018.
The field has been divided into three main flow units: Asgard, Mid Sands, and Basement. The sand quality in Asgard is superior to other flow units, although the net pay is low (an average of less than 5 m), leading to a smaller oil-in-place volume. Both the northeast of Mid Sands and Basement exhibit poor sand quality. Because the current recovery factor (RF) for Basement is less than 1%, the remaining oil compliant mapping (ROCM) workflow has not been implemented for this flow unit.
Almost half of the field’s production comes from the top three producers. More than 35% of the total field production originates from the six commingled wells. One of the top three producers is the largest commingled producer, perforated in Asgard and Mid Sands flow units. The kh multiplier and advanced allocation (AA) workflows are used for back-allocating historical production to the well and layer level. This advanced allocation workflow facilitates the generation of multiple realizations, incorporates surveillance data, and accommodates the variation in water-breakthrough times across different wells and layers.
The AA workflow conducted a multiphase allocation by seamlessly integrating a pseudosteady-state rate formulation with fractional flow modeling. This process incorporated permeability profiles at the well level and production logs into the allocation. An attempt was made to determine the water-cut (WCT) -evolution trend for each well-flow unit using a stochastic search engine, aiming to match total phase productions at the well level. This method was applied simultaneously across all wells and flow units, yielding individual production profiles for each well.