Electromagnetic Monitoring of Hydraulic Fracturing: Relationship to Permeability, Seismicity, and Stress

Thiel, Stephan

doi:10.1007/s10712-017-9426-2

Cited by 29 publications

(22 citation statements)

References 127 publications

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“…Due to its simplicity, the nonlinear sensitivity test is also widely used in other problems, such as analysis of the significance of different electromagnetic field components in resolving a given structure (Spies and Habashy 1995;Colombo and McNeice 2013), determination of minimum amplitudes of resistivity changes for resistivity monitoring (Didana et al 2017;Thiel 2017;Liu and Zoback 2017), evaluation of acquisition configurations (such as surface-to-surface or surface-to-borehole) (Wirianto et al 2010;Schamper et al 2011;Vilamajó et al 2013) or 4D time-lapse problems (Auken et al 2014; Rosas-Carbajal Fig. 9 Nonlinear sensitivity test for conductor C3 in a 3D MT inversion model of the Ordos Block (Dong et al 2014).…”

Section: Examples Of Nonlinear Model Analysesmentioning

confidence: 99%

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Ren

Kalscheuer

2019

Surv Geophys

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A meaningful solution to an inversion problem should be composed of the preferred inversion model and its uncertainty and resolution estimates. The model uncertainty estimate describes an equivalent model domain in which each model generates responses which fit the observed data to within a threshold value. The model resolution matrix measures to what extent the unknown true solution maps into the preferred solution. However, most current geophysical electromagnetic (also gravity, magnetic and seismic) inversion studies only offer the preferred inversion model and ignore model uncertainty and resolution estimates, which makes the reliability of the preferred inversion model questionable. This may be caused by the fact that the computation and analysis of an inversion model depend on multiple factors, such as the misfit or objective function, the accuracy of the forward solvers, data coverage and noise, values of trade-off parameters, the initial model, the reference model and the model constraints. Depending on the particular method selected, large computational costs ensue. In this review, we first try to cover linearised model analysis tools such as the sensitivity matrix, the model resolution matrix and the model covariance matrix also providing a partially nonlinear description of the equivalent model domain based on pseudo-hyperellipsoids. Linearised model analysis tools can offer quantitative measures. In particular, the model resolution and covariance matrices measure how far the preferred inversion model is from the true model and how uncertainty in the measurements maps into model uncertainty. We also cover nonlinear model analysis tools including changes to the preferred inversion model (nonlinear sensitivity tests), modifications of the data set (using bootstrap re-sampling and generalised cross-validation), modifications of data uncertainty, variations of model constraints (including changes to the trade-off parameter, reference model and matrix regularisation operator), the edgehog method, mostsquares inversion and global searching algorithms. These nonlinear model analysis tools try to explore larger parts of the model domain than linearised model analysis and, hence, may assemble a more comprehensive equivalent model domain. Then, to overcome the bottleneck of computational cost in model analysis, we present several practical algorithms to accelerate the computation. Here, we emphasise linearised model analysis, as efficient computation of nonlinear model uncertainty and resolution estimates is mainly determined by fast forward and inversion solvers. In the last part of our review, we present applications of model analysis to models computed from individual and joint inversions of electromagnetic data; we also describe optimal survey design and inversion grid design as important Extended author information available on the last page of the article applications of model analysis. The currently available model uncertainty and resolution analyses are mainly for 1D and 2D problems due to the limitation...

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Section: Examples Of Nonlinear Model Analysesmentioning

confidence: 99%

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Ren

Kalscheuer

2019

Surv Geophys

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“…When the scale of the fracturing layer is sufficiently large, the cumulative effect of multiple fracturing causes prominent anisotropic characteristics in the macroscopic formation. This has been confirmed in microseismic monitoring and experimental studies of petrophysical electrical properties (Thiel and Stephan, 2017). It is vital to study the TEM anisotropic response characteristics and effectively identify these characteristics during the fracturing monitoring process.…”

Section: Challenges Of 3d Forward Modelling For Hydraulic Fracturing ...mentioning

confidence: 76%

Development and Consideration of 3D Transient Electromagnetic Forward Modelling for the Hydraulic Fracturing Monitoring

et al. 2022

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“…For shale / unconventional application and reservoir monitoring, EM (mostly CSEM) response could yield more value than seismics in providing accurate information on the fluid properties. During the flooding operations, high-volume channels can gradually develop due to natural underground fractures, or they may occur suddenly, for example, with a hydraulic fracturing job [27]. EM monitoring methods, sometimes in combination with microseismic monitoring, can aid monitoring the reservoir seal during production.…”

Section: Introductionmentioning

confidence: 99%

An Array Multi-Physics Acquisition System with Focus on Reservoir Monitoring

Strack¹,

Paembonan²,

Davydycheva³

et al. 2021

Preprint

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Focusing geophysics to improve recovery factor of hydrocarbon reservoirs adds value and contributes toward ZERO carbon footprint by increasing the recovery factor by of 30-40 % and thus reducing the cost/carbon emission per produced barrel. Thus, the Enhanced Oil Recovery (EOR) market is expected to grow more than 3.5% annually. This will be even more fueled by the Green-House-Gas (GHG) reduction and subsequent CO2 injection into the reservoirs as they are being produced. Presently, geophysics only ac-counts for a small percentage of this market, thus its growth is inevitable since more deterministic observation lead higher operating efficiency. Imaging the fluids (hydro-carbon, water, and CO2) is a key component to optimized production and injection. We designed a novel electromagnetic (EM) acquisition system that combines mul-ti-physics fluid imaging and acquires surface and borehole data with high fidelity. Borehole calibration is needed to upscale reservoir data and parameters to measurement scale. Multiple electromagnetic methods are used as well as microseismics in one layout for Exploration and Production (E & P) problems. Multi-components in electromagnetics allows resolving oil and water-bearing zones equally well while achieving the best ac-curacy suitable for repeat measurements. Because sedimentary basins are intrinsically anisotropic, considering 3-dimensional anisotropy is essential from measurement and 3D modeling viewpoint. Thus, the results have the better subsurface images. Here, we combine hardware design, methodology, 3D modeling, processing, and interpretations into an integrated technology and demonstrate the success with verifiable case histories.

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Electromagnetic Monitoring of Hydraulic Fracturing: Relationship to Permeability, Seismicity, and Stress

Cited by 29 publications

References 127 publications

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Uncertainty and Resolution Analysis of 2D and 3D Inversion Models Computed from Geophysical Electromagnetic Data

Development and Consideration of 3D Transient Electromagnetic Forward Modelling for the Hydraulic Fracturing Monitoring

An Array Multi-Physics Acquisition System with Focus on Reservoir Monitoring

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