Condensate Banking Analysis Optimizes Reservoir Development in Permian Basin

Abstract

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 4044947, “Numerical Analysis of Condensate Banking and Development Optimization in the Deep Formation of the Permian Basin,” by Jichao Han, SPE, Sunil Lakshminarayanan, and Jiasen Tan, SPE, Oxy, et al. The paper has not been peer reviewed. _ In the context of unconventional reservoir development, the issue of condensate banking—a factor contributing to reduced productivity in gas condensate reservoirs when the reservoir pressure falls below the dewpoint pressure—poses a constant concern. Before implementation of any mitigation strategies, it is prudent to assess the potential of condensate banking in the future, based on the limited early production data. A specialized workflow was devised for a deep formation in the Permian Basin. This workflow aims to quantify the severity of condensate banking and subsequently optimize reservoir development strategies. Introduction Well A represents a single appraisal well situated within deep formations of the Permian Basin. With only 5 months of production data available, pressure/volume/temperature analysis and modeling identified it as a gas condensate reservoir, with the dewpoint very close to the critical point. This prompts two critical business inquiries: Are there any concerns regarding condensate banking for this well? And what are the optimal drawdown strategies tailored to this specific format surrounding the appraisal well? Model Setup and Calibration Modeling Workflow. This study uses the comprehensive simulation workflow derived from Hydraulic Fracturing Test Site 2, which can effectively handle integrated models to provide valuable insight for condensate banking analysis and reservoir development optimization (Fig. 1). Hydraulic fracture and reservoir simulations were conducted using GOHFER 3D and Navigator software, respectively. The integration of fracture and reservoir models poses a significant challenge in accurately transferring fracture geometry and conductivity information from fracture simulators to reservoir simulators. To address this challenge, an in‑house preprocessor was developed, designed to project results from the fracture simulator into the reservoir simulator seamlessly, ensuring the fidelity of complex fracture geometries. This preprocessor enables the extension or contraction of fracture geometries in proportion to reduce uncertainties imposed by production data. Additionally, fracture conductivity is determined through regional correlations among proppant concentration, net closure stress, and fracture conductivity. Model Introduction. The geological model has been simplified to enhance modeling efficiency while still meeting the project requirements. The 3D geological model adopts a layer-cake structure with a flat geostructure. To ensure accuracy, the well trajectory is adjusted to align with the desired formation. The reservoir model measures 4,000×10,000×330 ft, with a grid resolution of 200×25×10 ft. Fracture geometry is imported from the fracture simulator, while fracture conductivity is primarily determined based on proppant concentration data exported from the fracture simulator. Fracture height remains unaltered in the reservoir simulator, reflecting available geochemical measurements. A compositional simulation approach is adopted instead of a black-oil model. To improve the accuracy of pressure drop and condensate dropout predictions, the local grid refinement (LGR) approach is selected, resulting in denser grids. This approach proves superior to the dual-porosity, dual-permeability (DPDP) method.