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In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

In geophysical inversions, lower and upper model parameter bounds are a means of solution stabilization. Further, constraints that intend to let only geologically plausible inverse solutions pass are amenable to lower and upper bounds. Reliable prior information is paramount to construct such bound constraints. It is common practice to narrow and widen bound intervals for regions of, respectively, more and less certain prior information. Contrary to this practice, we experiment with widened bound intervals in zones that are poorly resolved by a given survey configuration but where prior information would suggest structural anomalies of interest. The purpose of enlarged parameter bounds that correlate spatially with predefined targets is to let the inversion explore a larger solution space, thus increasing the potential to resolve otherwise hidden anomalies. Application of the method is based on a carbon-sequestration baseline (pre-injection) crosswell electromagnetic (EM) field survey at the Containment and Monitoring Institute Field Research Station (Alberta, Canada), where impeded measurements led to generally reduced sensitivities for the interwell region. Synthetic-data proofs of concept use augmented bounds designed to boost the resolution of artificial plume targets, indicating an enhanced illumination compared to constant bounds. Comparative field data inversions with spatially variable bounds constructed from prior resistivity and velocity information highlight non-horizontal baseline structures.

A coupled approach, combining the theory of rate- and state-dependent friction and methods from poroelasticity, forms the basis for a quantitative relationship between displacements and fluid leak-off from a growing fracture and changes in the rate of seismic events in the region surrounding the fracture. Poroelastic Green's functions link fracture aperture changes and fluid flow from the fracture to changes in the stress field and pore pressure in the adjacent formation. The theory of rate- and state-dependent friction provides a connection between Coulomb stress changes and variations in the rate of seismic events. Numerical modeling indicates that the Coulomb stress changes can vary significantly between formations with differing properties. The relationship between the seismicity rate changes and the changes in the formation stresses and fluid pressure is nonlinear, but a transformation produces a quantity that is linearly related to the aperture changes and fluid leak-off from the fracture. The methodology provides a means for mapping changes in seismicity into fracture aperture changes and to image an evolving fracture. An application to observed microseismicity associated with a hydrofracture reveals asymmetric fracture propagation within two main zones, with extended propagation in the upper zone. The time-varying volume of the fracture agrees with the injected volume, given by the integration of rate changes at the injection well, providing validation of the estimated aperture changes.

Efficient and safe production of hydraulically fractured reservoirs benefits from the prediction of their geometrical attributes. Geophysical methods have the potential to provide data that are sensitive to fracture geometries, alleviating the typically sparse nature of in situ reservoir observations. Moreover, surface-based methods can be logistically and economically attractive since they avoid operational interference with the injection well infrastructure. This contribution investigates the potential of the surface-based time-domain electromagnetic (EM) method. EM methods can play an important role owing to their sensitivity to injection-induced fluid property changes. Two other advantageous factors are the EM signal-enhancing effect of vertical steel-cased wells and the fact that injected proppants can be enhanced to produce a stronger electrical conductivity contrast with the reservoir’s connate fluid. Nevertheless, an optimal fracture characterization will no doubt require the integration of EM and reservoir injection and production data. We hence carry out our investigations within a hydrogeophysical parameter estimation framework where EM data and injection flow rates are combined in a fully coupled way. Given the interdisciplinary nature of coupled hydrogeophysical inverse modeling, we dedicate one section to laying out key aspects in a didactic manner.

As motivation for considering new electromagnetic techniques for hydraulic fracture monitoring, we develop a simple financial model for the net present value offered by geophysical characterization to reduce the error in stimulated reservoir volume calculations. This model shows that even a 5% improvement in stimulated reservoir volume for a 1 billion barrel (bbl) field results in over 1 billion U.S. dollars (US$) in net present value over 24 years for US$100/bbl. oil and US$0.5 billion for US$50/bbl. oil. The application of conductivity upscaling, often used in electromagnetic modeling to reduce mesh size and thus simulation runtimes, is shown to be inaccurate for the high electrical contrasts needed to represent steel-cased wells in the earth. Fine-scale finite-difference modeling with 12.22-mm cells to capture the steel casing and fractures shows that the steel casing provides a direct current pathway to a created fracture that significantly enhances the response compared with neglecting the steel casing. We consider conductively enhanced proppant, such as coke-breeze-coated sand, and a highly saline brine solution to produce electrically conductive fractures. For a relatively small frac job at a depth of 3 km, involving 5,000 bbl. of slurry and a source midpoint to receiver separation of 50 m, the models show that the conductively enhanced proppant produces a 15% increase in the electric field strength (in-line with the transmitter) in a 10-Ωm background. In a 100-Ωm background, the response due to the proppant increases to 213%. Replacing the conductive proppant by brine with a concentration of 100,000-ppm NaCl, the field strength is increased by 23% in the 100-Ωm background and by 2.3% in the 10-Ωm background. All but the 100,000-ppm NaCl brine in a 10-Ωm background produce calculated fracture-induced electric field increases that are significantly above 2%, a value that has been demonstrated to be observable in field measurements. © 2015 European Association of Geoscientists

Electrical resistivity may contribute to progress in understanding geothermal systems by imaging the geometry, bounds and controlling structures in existing production, and thereby perhaps suggesting new areas for field expansion. To these ends, a dense grid of magnetotelluric (MT) stations plus a single line of contiguous bipole array profiling has been acquired over the east flank of the Coso geothermal system. Acquiring good quality MT data in producing geothermal systems is a challenge due to production related electromagnetic (EM) noise and, in the case of Coso, due to proximity of a regional DC intertie power transmission line. To achieve good results, a remote reference completely outside the influence of the dominant source of EM noise must be established. Experimental results so far indicate that emplacing a reference site in Amargosa Valley, NV, 65 miles from the DC intertie, is still insufficient for noise cancellation much of the time. Even though the DC line EM fields are planar at this distance, they remain coherent with the nonplanar fields in the Coso area hence remote referencing produces incorrect responses. We have successfully unwrapped and applied MT times series from the permanent observatory at Parkfield, CA, and these appear adequate to suppress the interference of the cultural EM noise. The efficacy of this observatory is confirmed by comparison to stations taken using an ultra-distant reference site east of Socorro, NM. Operation of the latter reference was successful by using fast ftp internet communication between Coso Junction and the New Mexico Institute of Mining and Technology, using the University of Utah site as intermediary, and allowed referencing within a few hours of data downloading at Coso. A grid of 102 MT stations was acquired over the Coso geothermal area in 2003 and an additional 23 stations were acquired to augment coverage in the southern flank of the first survey area in 2005. These data have been inverted to a fully three-dimensional conductivity model. Initial analysis of the Coso MT data was carried out using 2D MT imaging. An initial 3D conductivity model was constructed from a series of 2D resistivity images obtained using the inline electric field measurements (Zyx impedance elements) along several measurement transects. This model was then refined through a 3D inversion process. This model shows the controlling geological structures possibly influencing well production at Coso and correlations with mapped surface features such as faults and regional geoelectric strike. The 3D model also illustrates the refinement in positioning of conductivity contacts when compared to isolated 2D inversion transects. The conductivity model has also been correlated with microearthquake locations, well fluid production intervals and most importantly with an acoustic and shear velocity model derived by Wu and Lees (1999). This later correlation shows the near-vertical high conductivity structure on the eastern flank of the producing field is also a zone of increased acoustic velocity and increased Vp/Vs ratio bounded by mapped fault traces. South of the Devil's Kitchen is an area of high geothermal well density, where highly conductive near surface material is interpreted as a clay cap alteration zone manifested from the subsurface geothermal fluids and related geochemistry. Beneath the clay cap, however, the conductivity is nondescript, whereas the Vp/Vs ratio is enhanced over the production intervals. It is recommended that more MT data sites be acquired to the southwest of the Devil's Kitchen area to better refine the conductivity model in that area.

Because of their wide application within the petroleum industry it is natural to consider geophysical techniques for monitoring of CO2 movement within hydrocarbon reservoirs, whether the CO2 is introduced for enhanced oil/gas recovery or for geologic sequestration. Among the available approaches to monitoring, seismic methods are by far the most highly developed and applied. Due to cost considerations, less expensive techniques have recently been considered. In this article, the relative merits of gravity and electromagnetic (EM) methods as monitoring tools for geological CO2 sequestration are examined for two synthetic modeling scenarios. The first scenario represents combined CO2 enhanced oil recovery (EOR) and sequestration in a producing oil field, the Schrader Bluff field on the north slope of Alaska, USA. The second scenario is a simplified model of a brine formation at a depth of 1,900 m.

A finite-difference method for computing the first arrival traveltimes by solving the Eikonal equation in the celerity domain has been developed. This algorithm incorporates the head and diffraction wave. We also adapt a fast sweeping method, which is extremely simple to implement in any number of dimensions, to obtain accurate first arrival times in complex velocity models. The method, which is stable and computationally efficient, can handle instabilities due to caustics and provide head waves traveltimes. Numerical examples demonstrate that the celerity-domain Eikonal solver provides accurate first arrival traveltimes. This new method is three times accurate more than the 2nd-order fast marching method in a linear velocity model with the same spacing.

Cumulative oil predictions are made from stochastically inverted earth attributes. The inverted attributes are from the SEAM Life of Field model and an offshore field in West Africa. To perform the prediction, we use a naïve Bayesian classifier for its transparency in methodology, computational efficiency and flexibility. The inverted properties we use for classification consist of porosity, P‐S wave velocity ratio (Vp/Vs), acoustic impedance and density which are extracted from within a set radius around the well‐path. The production from the wells in both SEAM and the West African field serve as the labels for the naïve Bayesian classifier, which are ultimately placed into two classes: the 'high' and 'low' producers. For calculating the accuracy of the classifier, we perform full cross‐validation with a set number of training wells. The cross‐validation accuracy is 78.0% and 83.3% for the SEAM model and the West African Field respectively. The classifier's sensitivity to the chosen radius around the wells and its inherent independence assumption are investigated and shown to change the bulk accuracy by less than 3.0%. We implement full reservoir classifications on SEAM to highlight potential drilling locations and show the capability of the classifier. Overall, we demonstrate how the naïve Bayesian classifier can efficiently and transparently synthesize the entire distribution of stochastic inversions of seismic data to predict oil production. [ABSTRACT FROM AUTHOR]