Characterizing Well Spacing, Well Stacking, and Well Completion Optimization in the Permian Basin: An Improved and Efficient Workflow Using Cloud-Based Computing | SLB

Characterizing Well Spacing, Well Stacking, and Well Completion Optimization in the Permian Basin: An Improved and Efficient Workflow Using Cloud-Based Computing

Published: 07/23/2018

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In a multiwell environment, the formula for improving the recovery efficiency per rock volume depends on the well spacing, stacking, and the completion strategy. Operators in the multi-benched Permian basin have been actively pursuing various trials of different combinations of vertical and horizontal spacing and completions of the wellbores. The study presented in this paper tries to achieve a prescription for successful exploitation of the cube of the unconventional reservoir rock through cloud-based multivariate simulation modeling.

A multilayer Wolfcamp earth model was calibrated. Reservoir characterization for petrophysical and geomechanical properties and discrete natural fracture network (DFN) were the fundamental steps to build the calibrated earth model. The tools used to derive the optimal solution space included over 500 multithreaded streamlined cloud-based complex hydraulic fracture simulations, use of unstructured gridding, fine-resolution numerical simulations, and finite-element geomechanical simulations. Optimal well landing was achieved by using a full-3D hydraulic fracture simulator. The effects of varying proppant-per-foot design (1,000 lbm/ft to 5,000 lbm/ft.); cluster spacing, stage spacing, and various well spacing (300 ft to 1,500 ft) configurations; and vertically stacked and staggered configurations are studied.

From the study, it is demonstrated that there are four elements that contribute to maximizing the recovery factor: optimal well landing, optimal well completion, optimal well spacing, and optimal time of completion. The parent-to-child relationship impairs production by up to 18% in 1 year, which is exemplified though finite-element simulations capturing the stress magnitude and direction reorientation. Stimulation sequences such as zippering and non-zippering the wellbores for completion were also found to be critical. Multiple sensitivities have therefore allowed us to define the envelope for optimal strategy of asset development in the reservoir volume.

With cloud computing serving as the enabler, the methodology discussed in the case study provides an integrated workflow to optimize the completion strategy in a multilayered unconventional formation such as in the Permian basin. The workflow helps to derive a structured approach to minimize the development cost, increase well completion effectiveness, and minimize the bypassed leftover hydrocarbon in the reservoir.

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