Surface Microseismic Mapping Reveals Details of the Marcellus Shale

Hulsey, B.J.; Cornette, Brian Mitchell; Pratt, D.C.N.

doi:10.2118/138806-ms

Cited by 10 publications

(3 citation statements)

References 3 publications

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“…As such, it is used as a diagnostic tool for hydraulic fracturing treatments to infer the approximate extent and the orientation of the final fracture(s) [ Rutledge et al , ; Maxwell et al , ]. Few documented cases of the HF intersecting and potentially propagating along a well‐developed fault (scenario (1) and (2i) in the above) within the hydraulically fractured reservoir [ Hulsey et al , ; Wolhart et al , ] showed a tendency for increased count and magnitude of events associated with the reservoir fault yet still remaining within the microseismic realm (negative seismic moment magnitude).…”

Section: Field Implicationsmentioning

confidence: 99%

Nucleation of dynamic slip on a hydraulically fractured fault

2017

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This work is concerned with the relationship between hydraulic fracturing injection into a fault and the possibility of a seismic slip. The results of this study show that the nucleation of dynamic slip on a fault with slip‐weakening friction is only weakly dependent on the magnitude of the stress perturbation ahead of the propagating hydraulic fracture (HF), or the HF propagation regime, and is mainly controlled by the hydraulic fracture length (i.e., the size of the fully unloaded fault segment at a given time). The growth of the fault slipping patch remains stable when the background shear stress τ0 is smaller than the residual fault strength τr under ambient conditions. Otherwise (τ0>τr), nucleation of dynamic slip takes place when the hydraulic fracture grows to the critical size ℓc, which is vanishingly small ∝τp−τ0 for critically stressed faults (i.e., when the background stress approaches the fault peak strength, τ0→τp) and is diverging as ∝1/(τ0−τr) when the stability boundary is approached ( τ0→τr). Our solution for the critical HF size allows to infer the corresponding fluid injection volume that may lead to slip instability on a fault with given frictional properties and background stress.

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Section: Field Implicationsmentioning

confidence: 99%

Nucleation of dynamic slip on a hydraulically fractured fault

2017

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“…Case 2,-The second case is a vertical hydraulic fracture created in a horizontal gas well drilled in the Marcellus shale. The microseismic monitoring data for hydraulic fracturing stage 5 was published by Hulsey et al (2010). However there were 6 hydraulic fracturing stages.…”

Section: Case Studiesmentioning

confidence: 99%

3D Analytical Modeling of Hydraulic Fracturing Stimulated Reservoir Volume

Aguilera

2012

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An easy to use analytical 3D model is developed to simulate the growth of stimulated reservoir volume (SRV) with time once a hydraulic fracturing job is started in an anisotropic poroelastic medium. In the proposed method, diffusivity coefficients in three dimensions are determined first by calibrating the model with an actual 3D microseismic-event cloud. Then the geometry of SRV is predicted under different stimulation conditions. The method permits studying the geometry of hydraulic-fracturing SRVs in both vertical and horizontal wells. The analytical model is corroborated with the use of a numerical simulator. The proposed method is important because in unconventional low-permeability reservoirs, such as shale and tight gas reservoirs, productivity depends primarily on permeability of the SRV and the reservoir area contacted by the SRV. Microseismic monitoring has been shown to be a useful technology to study the characteristics of hydraulic fractures. As such, the optimum is to constrain the analytical 3D model developed in this study with the use of microseismic data. It is concluded that this easy to use, yet accurate analytical model, is a viable tool for analyzing the orientation and geometry of hydraulic-fracturing SRV and for predicting other SRVs in the same reservoir. Examples of applications which can be reproduced easily in a spread sheet are presented in detail.

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“…Discrete fracture networks often link microseismic event trends to pre-existing fault reactivation and the orientation of S Hmax (Maxwell et al 2002, Hulsey et al 2010. These patterns are also characteristic of the Barnett Shale, in which the study took place (Gale et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Refining Discrete Fracture Networks With Surface Microseismic Mechanism Inversion and Mechanism-Driven Event Location

2012

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Microseismic event analysis is a valuable source of information that can play a pivotal role in optimizing well completion and spacing. This analysis can be taken a step further with the generation of discrete fracture networks (DFNs) from microseismic events. While DFNs can be modeled with microseismic event locations only, source mechanisms inverted from near surface-acquired microseismic data provide greater constraints for the DFN model so that the orientation of failure planes responsible for events can be explicitly assigned. The differences between such DFN realizations based on event locations only and source-mechanism constrained DFN realizations are evident in areas with significant geological complexity.Three iterations of a DFN model were produced from a microsesimic monitoring project in the Barnett shale. The fracture network of the first iteration is modeled stochastically using only basic geologic assumptions for the area and microseismic event locations and the orientations of trends formed by the events. The second iteration is refined by deterministically locating fractures in the model and defining the fracture orientations using a source mechanism determined from the microseismic point set. The third iteration uses the results from a mechanism scan on an event per event basis to determine the best source mechanism that fits the polarity reversal signature observed on the surface array.Refining the model by determining the mechanism of individual events can identify multiple fracture orientations within the point set. In this data set two distinct mechanisms were identified, further analysis of which identified separate event energy distributions for the two mechanisms.The changes in the model can be quantitatively evaluated with analysis of flow properties generated from the DFN and output to the stimulated reservoir volume (SRV). While changes in the SRV and total fracture volume for models presented in this study are most significant between the first two iterations, the total permeability change across the geocellular volume is significant between all three iterations.

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Surface Microseismic Mapping Reveals Details of the Marcellus Shale

Cited by 10 publications

References 3 publications

Nucleation of dynamic slip on a hydraulically fractured fault

Nucleation of dynamic slip on a hydraulically fractured fault

3D Analytical Modeling of Hydraulic Fracturing Stimulated Reservoir Volume

Refining Discrete Fracture Networks With Surface Microseismic Mechanism Inversion and Mechanism-Driven Event Location

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