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Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗

Diagnostic assessment of reservoir response to fracturing: a case study from Hydraulic Fracturing Test Site (HFTS) in Midland Basin

Abstract This paper outlines a data collection and diagnostics case study involving multiple horizontal shale wells. We look at well production profiles using rate transient analysis, differences in near wellbore complexity, geologic variations within the area of interest, as well as compositional differences in the rocks based on cores obtained from within the stimulated reservoir. The Hydraulic Fracturing Test Site is a multi-well experiment involving stimulation of unconventional shale wells in the southeastern Midland portion of the Permian Basin. The targeted formations include both the upper as well as the middle Wolfcamp formations, also referred alternatively as Wolfcamp A and Wolfcamp B. Data integration and analysis shared in this paper help us understand the various geologic controls impacting well productivity, particularly the wide variance observed between the Wolfcamp A and Wolfcamp B formations. Rate transient analysis indicates similar system permeabilities for stimulated wells. However, we observe higher effective fracture half-lengths for upper Wolfcamp wells. Using observations from 3D seismic interpretations (such as pad scale faults) as well as petrophysical and image log data, we highlight the substantial differences in stimulation as we move along the well laterals from the heel toward the toe sections. These differences are further reconciled with observations from zones with high data density at the core locations through stimulated rock, as well as independent data such as microseismic emissions. At the test site, Wolfcamp A was found to be relatively quartz rich with significant heterogeneity whereas Wolfcamp B is richer in clay and organic content. This impacts the geomechanical characteristics of the rock mass with much higher natural fracture density in the shallower interval. Thus, the fracture growth is more uniform in the deeper interval and more heterogeneous with branching likely in upper interval. Increased complexity also leads to consistently better productivity from the wells in the shallower interval as demonstrated from RTA results. This case study is unique because it provides valuable insights from actual sampling of the stimulated zones in hydraulically fractured wells and helps understand impact of various factors that contribute toward variability in well production. The findings from this study provides insights into need for optimization of completion designs in the various Wolfcamp landing zones, such as optimization of cluster or fracture spacing in various Wolfcamp intervals. In addition, it provides a useful template for data collection and research direction in future field test sites of similar nature in unconventional reservoirs.

Energy & Fuels↗

Developing Upscaling Approach for Swarming Hydraulic Fractures Observed at Hydraulic Fracturing Test Site through Multiscale Simulations

We show that this work aims to address a challenge posed by recent observations of tightly spaced hydraulic fractures in core samples from the hydraulic fracturing test site (HFTS) in the Middle Wolfcamp Formation. Many fractures in retrieved cores have subfoot spacing, which is at odds with conventional models in which usually one hydraulic fracture is initiated per cluster. Models assuming a single fracture at each cluster, although a common practice, often predict excessive fracture propagation that is inconsistent with microseismic observation. Here, we aim to develop a numerical approach to effectively account for densely spaced hydraulic fractures in field-scale simulations. Because it is impractical to explicitly model all aforementioned fractures, we develop a new upscaling law that enables existing simulation tools to predict reservoir response to fracture swarms. The upscaling law is derived based on an energy equivalence argument and validated through multiscale simulations using a high-fidelity code, GEOS. The swarming fractures are first modeled with a spacing that is much smaller than the cluster spacing; these fractures are then approximated by an upscaled, single fracture based on the proposed upscaling law. The upscaled fracture is shown to successfully match the energy input rate and produce the total fracture aperture and average propagation length of the explicitly simulated swarm. Afterward, the upscaling approach is further implemented in 3D field-scale simulations and validated against the HFTS microseismic data of a horizontal well. Our results show that hydraulic fracture swarming can significantly affect fracture propagation behaviors compared with the propagation of single fractures as assumed by conventional modeling approaches. Under the considered situations, the conventional treatment yields fast propagation speed that far exceeds that indicated by the microseismic data. We also illustrate that this discrepancy can be reduced readily through the implementation of the upscaling law. Our results demonstrate the importance of accounting for the fracture swarming effect in field-scale simulations and the efficacy of this approach to enable realistic predictions of reservoir responses to fracture swarms, without the need to model tightly spaced fractures individually.

02 PETROLEUM↗

Deep Learning–Assisted Multiobjective Optimization of Geological CO 2 Storage Performance under Geomechanical Risks

In geological CO 2 storage, designing the optimal well control strategy for CO 2 injection to maximize CO 2 storage while minimizing the associated geomechanical risks is not trivial. This challenge arises due to pressure buildup, CO 2 plume migration, the highly nonlinear nature of geomechanical responses to rock-fluid interaction, and the high computational cost associated with coupled flow and geomechanics simulations. In this paper, we introduce a novel optimization framework to address these challenges. The optimization problem is formulated as follows: maximize total CO 2 storage while minimizing geomechanical risks by adjusting the injection schedules within bounded constraints. The geomechanical risks are primarily driven by injection-induced pressure build-up, which is characterized by ground displacement and the induced microseismicity. We used the Fourier neural operator (FNO)-based deep learning model to construct surrogate models, replacing the time-consuming coupled flow and geomechanics simulations for evaluating the aforementioned objective functions. The developed surrogate models have been incorporated into a multiobjective optimization framework through a genetic algorithm to reduce the computational burden. The proposed optimization framework reduces the computational cost from approximately 2,400 hours, when using objective function evaluations based on physics-based simulations, to around 20 minutes. A set of Pareto-optimal solutions of the proposed workflow yields nontrivial optimal decisions, reducing the microseismicity potential and the vertical displacement. This Pareto front highlights the optimal trade-offs between CO 2 storage amount, safety, and ground displacement, emphasizing the need for careful optimization and management of injection strategies to achieve a balanced outcome. The novelty of this work is twofold. First, we demonstrate the importance of incorporating the minimization of the geomechanical risks as objective functions into the CO 2 storage optimization workflow to mitigate the potential risk of induced microseismicity and ground displacement. Second, we leverage the FNO-based surrogate models to optimize a real-field CO 2 storage operation.

42 ENGINEERING↗

HFTS-1 (Final Report)

Despite the long history of hydraulic fracturing, the optimal number of fracturing stages during multi-stage fracture stimulation in horizontal wells can be a complex subject. In addition to the increased expense of multistage fracturing in horizontal wells, increasing the number of fracturing stages does not always correlate with a commensurate increase in production. The problem is the application of a uniform fracture stimulation design to all stages with no consideration for geological variations along the wellbore. The result is an inefficient use and costly waste of energy and water. Optimization of the fracturing process requires an understanding of the cause-and-effect relationship between fracturing parameters and local geological properties at a given location along the wellbore. Realizing that the generalized rock mechanics theories and hypotheses are not truly applicable to fractured and laminated shales, quantifiable impacts of a shale’s geomechanical and depositional features are a prerequisite for design and implementation of optimized hydraulic fractures. The overarching goal of this project is to understand and define the relationships of shale geology and fracture dynamics using detailed field data that includes coring of the fracture domain. Finally, resource recovery from shale formations is estimated to be less than fifteen percent. Research proposed in this project will establish the foundations for investigating enhanced recovery techniques for increased resource recovery in existing fracture treated wells. Natural gas as an EOR fluid is in the initial stages of being used broadly in the oil and gas industry and as such, many aspects of the process need to be researched and addressed prior to widespread acceptance. In addition, re-fracturing techniques, particularly using cemented liners also need to be further investigated. This project explores several of these EOR techniques in greater detail, not just at the theoretical level, but through actual field test sites. This report delves into the research program, identified tasks, several studies, observations, results, and conclusions under the Hydraulic Fracturing Test Site (HFTS) project. This test project is subdivided into three distinct phases and each phase is discussed in detail under separate sections. The original test site for Phase 1 as well as the Phase 2 site are in Midland Basin in Texas and operated by Laredo Petroleum. In the first two phases, the program targeted the Wolfcamp formation in Midland Basin. Phase 3 of the study targeted the EagleFord play in South Texas with Devon Energy as the operator. Significant conclusions from this study include: 1) lateral and vertical fracture growth mapping as well as proppant transport behavior, 2) Use of field gas and its applicability for huff n puff EOR injection in the Midland Basin, 3) Development and validation of proppant log, both at core scale as well as in-fill well implementation by analyzing drilling mud return samples, 4) Applicability of liner refracturing including best practices for enhanced unit level productivity. This report will detail all these studies as well as technical results and conclusions from said studies. These include general subsurface characterization work, completion designs as implemented, studies looking at fracture geometry, high resolution microseismic study, advanced crosswell strain mapping studies including drainage characterization, core characterization results, proppant analysis (core and observation wells), geochemistry, etc. to name a few.

02 PETROLEUM↗