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Extraction of unconventional energy has become a major global industry in the last decade and is driven by changes in technology and increasing demand. One of the key factors for the success of gas extraction is establishing sufficient permeability in otherwise low-porosity and low-permeability formations. Permeability can be established through hydraulic stimulation of deep formations, either through existing fracture networks or by creating new pathways for fluids to flow, and through depressurization of coalbeds by extracting existing subsurface fluids. Geophysical monitoring of hydraulic stimulation and depressurization can be used to determine lateral and vertical constraints on fluid movements in the target lithologies. Such constraints help to optimize production and well placement. In addition, independent verification is critical for social and environmental regulation, to ensure that hydraulic stimulations and depressurization do not interact with overlying aquifers. To date, the primary and most successful geophysical technique has been microseismic, which measures small seismic events associated with rock fractures from arrays of surface and downhole geophones. The microseismic approach has been used widely for many types of unconventional energy-resource development. The magnetotelluric (MT) method is an alternative approach to monitoring hydraulic stimulations and depressurization. In contrast to microseismic, which delineates the locations of rock fractures, MT is sensitive directly to the presence of fluid as measured by the earth's bulk electrical resistivity, which is dependent on permeability. MT is sensitive to the direction of fluid connection, so it might yield important information on how fluids migrate with time. Because subsurface fluids conduct electrical current dependent on the porosity, connectivity, and ionic saturation of the fluid, it follows that the introduction or removal of fluids will change the electrical resistivity of the formation. The physics of the approach is outlined, and the feasibility of the MT method for monitoring unconventional energy-resource development is demonstrated. Two case studies are conducted, one for a shallow (CSG) depressurization and the second for a deep hydraulic stimulation of a shale-gas reservoir.

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The telluric sounding (TS) method is introduced as a potential tool for monitoring hydraulic fracturing at depth. The advantage of this technique is that it requires only the measurement of electric fields, which are cheap and easy when compared with magnetotelluric measurements. Additionally, the transfer function between electric fields from two locations is essentially the identity matrix for a 1D Earth no matter what the vertical structure. Therefore, changes in the earth resulting from the introduction of conductive bodies underneath one of these sites can be associated with deviations away from the identity matrix, with static shift appearing as a galvanic multiplier at all periods. Singular value decomposition and eigenvalue analysis can reduce the complexity of the resulting telluric distortion matrix to simpler parameters that can be visualised in the form of Mohr circles. This technique would be useful in constraining the lateral extent of resistivity changes. We test the viability of utilising the TS method for monitoring on both a synthetic dataset and for a hydraulic stimulation of an enhanced geothermal system case study conducted in Paralana, South Australia. The synthetic data example shows small but consistent changes in the transfer functions associated with hydraulic stimulation, with grids of Mohr circles introduced as a useful diagnostic tool for visualising the extent of fluid movement. The Paralana electric field data were relatively noisy and affected by the dead band making the analysis of transfer functions difficult. However, changes in the order of 5% were observed from 5 s to longer periods. We conclude that deep monitoring using the TS method is marginal at depths in the order of 4 km and that in order to have meaningful interpretations, electric field data need to be of a high quality with low levels of site noise.