Abstract

Reservoir models are critical represent the static and dynamic properties of a sub-surface zone of interest in order to assess in place and recoverable resources in conventional and more recently unconventional plays. For Shale and Tight (S&T) systems, more traditional methodologies have been applied for trendology through variograms and combining object-based modeling for rock property population. Although these traditional approaches address key needs for model generation, significant gaps exist due to stratigraphic heterogeneity in rock properties that is often not adequately represented within the geologic framework or exists below the resolution of the data. These lessons learned instructed a novel approach in modeling through physics-based Computational Stratigraphy that provides an ultra-high-resolution digital framework (depositional bed-scale) for conditioning geologic layering and variance in grain-size associated with depositional process.

The Permian Basin Wolfcamp A was first tested for this workflow, as deepwater unconfined distributary lobes were modeled in a predictable depositional framework using Computational Stratigraphy. Computational Stratigraphy outputs were used to construct the geologic framework (k-layers) to represent compensational stacking of distributary lobes with at the regional scale to provide guidance for property population with internal decay of rock quality within lobe elements. This methodology contrasts strongly with larger-scale "layer-cake" packages with high lateral continuity. Furthermore, Computational Stratigraphy provides multiple scenarios for a given depositional setting for sensitivity analysis and provides ranges of simulations to understand range and magnitudes of uncertainty and reduces interpreter-bias. This workflow provides a step-change for reservoir modeling for S&T due to the geologic conformance with predicted depositional environment, stratigraphic architecture, heterogeneity, and facies distribution.

Introduction

Exploration of shale & tight (S&T) plays in the Permian Basin of West Texas has become a prioritized focus for the industry. A primary research topic in industry and academia is identifying the fundamental controls on well performance, whether it be linked to operational (i.e., completion design, proppant, well spacing, etc.) or geologic factors (e.g., sequence stratigraphy, geomechanics, thermal history, facies distribution, fracture development). Whilst there does not appear to be a single attribute uniquely linked to productivity, rock properties associated with facies development and distribution appears to be one of the primary controls (Passey et al., 2010; Mohan et al., 2013; Wilson and Schieber, 2016; Wilson et al., 2020; Wilson et al., 2022; Bohacs et al., 2023).

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