Hydraulic fracturing is a widespread well stimulation treatment in the oil and gas industry. It is particularly prevalent in shale gas fields, where virtually all production can be attributed to the practice of fracturing. It is also used in the context of tight oil and gas reservoirs, for example in deep-water scenarios where the cost of drilling and completion is very high; well productivity, which is dictated by hydraulic fractures, is vital.

The correct modeling in reservoir simulation can be critical in such settings because hydraulic fracturing can dramatically change the flow dynamics of a reservoir. What presents a challenge in flow simulation due to hydraulic fractures is that they introduce effects that operate on a different length and time scale than the usual dynamics of a reservoir. Capturing these effects and utilizing them to advantage can be critical for any operator in context of a field development plan for any unconventional or tight field.

This paper focuses on a study that was undertaken to compare different methods of simulating hydraulic fractures to formulate a field development plan for a tight gas field. To maintaing the confidentiality of data and to showcase only the technical aspect of the workflow, we will refer to the asset as Field A in subsequent sections of this paper. Field A is a low permeability (0.01md-0.1md), tight (8% to 12% porosity) gas-condensate (API ~51deg and CGR~65 stb/mmscf) reservoir at ~3000m depth. Being structurally complex, it has a large number of erosional features and pinch-outs.

The study involved comparing analytical fracture modeling, explicit modeling using local grid refinements, tartan gridding, pseudo-well connection approach and full-field unconventional fracture modeling. The result of the study was to use, for the first time for Field A, a system of generating pseudo well connections to simulate hydraulic fractures. The approach was found to be efficient both terms of replicating field data for a 10 year period while drastically reducing simulation runtime for the subsequent 10 year-period too. It helped the subsurface team to test multiple scenarios in a limited time-frame leading to improved project management.

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