A new workflow that uses the strain derived from geomechanical modeling of hydraulic fractures interacting with natural fractures is applied to an Eagle Ford well. The derived strain map is used to estimate the asymmetric half lengths that are input in any frac design software able to incorporate this new information. The simplistic symmetric and bi-wing design is revised by adjusting the leakoff coefficient, injection rate, and proppant concentration resulting in asymmetric half lengths that do not exceed the lengths of those provided by the strain map. Once the half lengths and orientation from the frac design match those provided by geomechanical simulation, the propped length and other key results provided by the frac design software may be used to optimize the well's completion. This process could be used iteratively to optimize desired metrics and could also be used to improve reservoir simulation. The derived strain map may be propagated in the stimulated geomechanical layer to form a strain volume which may in turn be used to estimate the stimulated permeability. In this paper, we used a radial function to relate the stimulated permeability to the strain within the maximum half lengths provided by the strain map. Two calibration constants are needed in the radial functions and could be estimated by history matching or pressure transient analysis. An adaptive Local Grid Refinement (LGR) and variable stimulated permeability provide a realistic representation of the stimulated reservoir volume (SRV). After history matching, the resulting pressure distribution allows an accurate selection of refrac or new well candidates, for optimizing well spacing, and for estimating an accurate EUR.
Optimizing a well's hydraulic fracture design within a pad development environment is a multi-disciplinary effort and requires a 4-dimensional understanding of the reservoir. This paper presents a workflow that uses an integrated workflow that combines geology, and geomechanics to build a reservoir model which can be interrogated and updated with a geologically and geomechanically constrained grid-based 3D planar frac model and production simulation using a fast marching method. In this case, as applied to an Eagle Ford well to address concerns of completion optimization, production and depletion forecasting, well spacing and well interference. The workflow captures the variability of stresses and rock properties along the wellbore and around it by using multiple geologic and geomechanical approaches. The estimated variability of rock mechanical properties is used as input in a 3D planar frac simulator. An alternative approach to geoengineering a completion, using the differential stress derived from geomechanical simulation that overcomes the limitations of well centric methods, is also illustrated. The frac design results are used as inputs/constraints in a new reservoir simulator that was developed using the Fast Marching Method to estimate drainage area. This allows for a constrained, yet extremely fast estimate of the EUR and resulting pressure depletion, addressing the important concerns of well spacing optimization and prevention of frac hits and well interferences, all in a timely manner. The integrated approach facilitates adaptive frac design which honors in-situ conditions including stress field heterogeneity, stress shadow effects and the pressure depletion from nearby producing wells. The proposed workflow enables greater investment efficiency and promotes field development optimization.
This paper describes the application of a workflow that uses Geophysics, Geology, and Geomechanics (3G) for completion optimization. The 3G workflow relies on the modeling of the interaction between hydraulic and natural fractures to estimate key reservoir properties that could be used to better understand data such as microseismicity or to plan an engineering completion. The 3G workflow uses geomechanical simulation that combines the meshless Material Point Method (MPM) with Continuous Fracture Modeling (CFM). The distribution of the natural fracture density is estimated from G&G data and in this paper it uses a time lapse 3C seismic that was processed for Shear Wave Velocity Anisotropy (SWVA). The geomechanical workflow uses this as an input to predict quickly over a large area the Normalized Differential Horizontal Stress (NDHS) and the Maximum Horizontal Stress Direction (MHSD) maps. Both these properties are used to improve the interpretation of microseismicity and to provide valuable information for the completion engineer to optimize his frac design. When using this approach on a Montney two wells pad, it appears that high values of NDHS are directly correlated to the fracture density estimated from the shear wave splitting parameter. While the local direction of maximum horizontal stress generally follows the direction of the imposed regional stress, large stress rotations of up to 90 degrees could occur in areas where the NDHS is very high. This observation is validated with microseismic data that confirms the local development of axial fracs instead of the desired transverse hydraulic fractures. Combining the NDHS and MHSD maps will be a very valuable completion optimization tool that would assist the completion engineer in adapting his frac design and treatment to the local geomechanical environment. The same 3G workflow will also provide to the completion engineer with quantitative tools such as the strain distribution and the J integral to predict or evaluate the efficiency of multiple fracing sequences and understand what is happening in the field experiments frequently showing zipper fracs outperforming other fracing sequences.
This paper presents a new integrated workflow that couples geology, geomechanics and geophysics (3G) with a constrained asymmetric frac model as applied to a Wolfcamp well to address the concerns of well interference. The proposed workflow enables the ability to adapt the frac design of each stage based on the in-situ geologic and geomechanical variability. The objective of this approach is to identify the variable treatment parameters required to overcome the stress heterogeneity and estimate the impact of the adaptive frac design on the final fracture geometry. The lateral stress gradients resulting from the pressure depletion due to a nearby producing well and the fluid leak-off due to opening of natural fractures are fine-tuned to account for asymmetry observed in the geomechanical modeling. The role of the natural fractures is emphasized and practical approaches to estimate a validated natural fracture model are described and illustrated. A validation well is used to highlight the importance of the input natural fracture model in calculating validated differential stress and strain that reproduce the main features of the microseismic. With this validated strain model, a constrained frac design provides the proper asymmetric fracture geometry able to pinpoint the poor and good frac stages. Once the workflow is extensively validated, it can be used on target wells to avoid frac hits. In this Wolfcamp example, the challenge was to find the optimal frac design to minimize interference of an infill well with existing offset producers. To address the possible zones of interference, the stage spacing was locally increased to 152 m (500 ft), and the treatment was especially modified in the middle stages of the well. This resulted in reducing the number of stages from 40 to 34, specifically in zones indicating high probability of interference. The design was altered from pumping a mixture of 320,000 lb of 100 mesh and 40/70 mesh sand to 220,000 lb of 40/70 mesh sand, and the injected fluid viscosity was increased from 10 centipoise (cP) for slick water to 30 cP for linear gel as better carrying capacity was required to pump only 40/70 mesh sand. Additonally, the injection rate was reduced from 105 bbl/min to 80 bbl/min. The integrated approach allows for the ability to adapt the frac design to in-situ conditions including heterogeneity in the stress fields and the pressure depletion from existing producers. Adaptive frac design significantly reduces the probability of frac hits and well interference. The proposed modeling workflow enables greater investment efficiency and overall field development optimization.
Predictable well performance is a key factor for the economic development of unconventional reservoirs including tight sands, tight carbonates and shales. A factory approach to developing unconventional reservoirs has resulted in unpredictable and highly variable well performance, much of which has been uneconomic. Minimizing the uncertainty in production forecasting and reservoir simulation necessitates an accurate model, which captures the interaction of induced hydraulic fractures with existing natural fractures. One method to achieve this is by using a 3G workflow, which leverages the synthesis of geophysical and geological information through geomechanical techniques to model the hydraulic fracturing of unconventional reservoirs. A complete workflow is presented for modeling and simulation of unconventional reservoirs, which incorporates the characterization of natural fractures and their interaction with hydraulic fracture stimulation. The 3G workflow is applied to an unconventional well in the Wolfcamp Shale, Permian Basin. The geomechanical modeling results are exported to a standard commercial numerical reservoir simulator using two different approaches; strain volume and constrained asymmetric hydraulic fractures. A third reservoir simulation case is created in which commonly used symmetric hydraulic fractures are generated without any external geomechanical model. An automated history matching tool is used to find the hydraulic fracture parameters for this over simplistic and unrealistic case. The production forecast and pressure depletion profiles are compared for all three cases. The proposed unconventional modeling workflow is not only fast but also significantly reduces uncertainty in the reservoir simulation results, improving reliability of the production forecast as well as the pressure depletion profile. These constrained simulations provide the information necessary to make better decisions in field development planning.
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