Sparse CSEM inversion driven by seismic coherence

In controlled-source electromagnetic (CSEM) inversion with conventional regularization, the reconstructed conductivity image is usually blurry and only has limited resolution. To effectively obtain more compact conductivity models, we apply the concept of multinary transformation to CSEM inversion based on the finite-element method with an unstructured tetrahedral mesh. Within the framework of multinary inversion, the model conductivities are allowed to be clustered only within the designed values, which are usually obtained from other a priori information or from conventional inversion. Synthetic studies show that multinary inversion produces conductivity images with clearer model boundaries compared to the maximum smoothness inversion and the focusing inversion for realistic geoelectric models. We further apply the developed method to a land CSEM survey for mineral exploration. The multinary inversion results are closer to the ground truth compared to the conventional maximum smoothness inversion and the focusing inversion. The developed method and the numerical algorithm provide a new approach and workflow for CSEM inversion when the models need to have clear boundaries and clustering model values. Such geoelectric models could be very useful for geologic interpretation in oil and mineral exploration when a priori information (such as the estimated conductivity values) of the exploration targets is known.

Since the late 1990s, the continuous development and application of the Controlled-Source Electromagnetic (CSEM) technology have vastly improved its usage in exploration (e.g., Constable, 2010; Loseth et al., 2015; Zach et al., 2009). CSEM inversion results are the main input for interpretation of resistivity data, especially potential fluid anomalies. Complementary to other geophysical methods, e.g. Amplitude versus Offset (AVO), it can therefore be a valuable tool in hydrocarbon exploration. Yet, the unconstrained nature of the subsurface and non-unique¬ness of inversions is a tough predicament. For example, several features in the subsurface could cause high resistivity, such as abundant limestone, salt, basalt, mature source rocks or hydro¬carbon-filled sandstones (Baltar and Barker, 2015). As a result of enhanced data quality, data processing and inversion capabilities, together with improved workflows and accumulated experience, CSEM interpretation has become increasingly more robust (Buland et al., 2011; Karman et al., 2013; Loseth et al., 2014). The 3D Gauss-Newton (GN) inversion algorithm is a more robust method compared to other inversion types. GN thus provides a new, powerful methodology for generating marine CSEM resistivity images. Nonetheless, it has formerly been com¬putationally exhaustive to apply. With the Hoop area, Barents Sea, recently being nominated for the Barents Sea exploration licensing round, a tight deadline was given for the CSEM inversion of an expansive 11,000 km2, over 130 blocks (refer to Figure 1). Adopt¬ing the flexible and agile cloud system into the CSEM workflow, it has improved the 3D GN work efficiency and provided overall consistent results when compared with other CSEM inversion schemes. This paper will illustrate how a systemic workflow of CSEM 3D GN inversions together with efficient cloud computing, could lead to a more consistent interpretation of this data.

In August 2008, a marine Controlled Source ElectroMagnetic (CSEM) survey was acquired by WesternGeco EM for the previous operator (Encana) of Lady Franklin and Atammik blocks offshore west Greenland. The objective of the project was to rank possible hydrocarbon prospects in the upper Cretaceous section. Therefore, the survey was designed to optimize CSEM responses based on the previous operator's interpretation within a limited budget, resulting in a pseudo-3D survey, sub-optimal to assess actual interpretation updated according to the results of the three exploration wells drilled by Cairn in the block during 2011. Independent 3D inversions of the CSEM data run before the drilling campaign suggest a consistent background resistivity over the different prospects. Drilling results confirmed the resistivity distribution as recovered by 3D CSEM inversions within the data resolution limit. After the drilling campaign, a sensitivity study was carried out in order to assess the limit at which the geological problem can be tuned by the electromagnetic data response. This showed that the resistive anomalies visible on some of the prospects in the block cannot be assessed for hydrocarbon saturation on the basis of electromagnetic data alone as they are below the resolution of the method given the non-uniqueness of the results. The present paper highlights how non-seismic data, such as electromagnetic, can provide additional information which, integrated with other geophysical and geological data, can help exploration during the different phases. The pre-drilling analysis of the resistivity distribution as recovered by 3D inversion of the data identified resistive anomalies that were interpreted as hydrocarbon indicators. The drilling results identified the geological meaning of these anomalies, which were further analyzed to include and extrapolate the new post-drilling interpretation in order to evaluate the non-drilled prospects. The sensitivity study was critical to understand the EM data limitations in this geological context before investing in a new project. Introduction Electromagnetic data are widely applied in the oil industry in order to de-risk exploration, reducing the uncertainty related to reservoir saturation (Hesthammer et al., 2012). Many success stories increased the confidence in electromagnetic data as hydrocarbon detectors: in fact, electromagnetic data provide information exclusively regarding the resistivity distribution of the underlying earth. Resistive anomalies may be related to fluid saturation, but they may also be produced by different geological features not necessarily related to fluid saturation: volcanics, carbonates, and evaporites are only some examples of lithologies characterized by high resistivity values. In addition, inversion of electromagnetic data is a non-unique problem and therefore constraining the inversion with the available geological and geophysical information is critical in order to produce a geologically meaningful model and subsequent interpretations. The limited data and frequency range (~ 0.1 to 10 Hz), the diffusive physics of CSEM, and the necessity (usually) of using a smooth stabilizer for inversion result in low resolution.

To improve the interpretation of controlled‐source electromagnetic (CSEM) data it is desirable to include information from seismic data in a joint interpretation. The higher resolution of the seismic image makes it possible to accurately determine the depth of resistivity contrasts detected by the CSEM data. In this paper we show how horizons derived from seismic data can be incorporated in a CSEM inversion workflow to obtain resistivity models which are more consistent with both the CSEM data and the seismic data, and we demonstrate this workflow on a CSEM field data set.

Integrated analysis of well, seismic and controlled source electromagnetic (CSEM) data is key in order to provide valuable information on reservoir properties and content. The purpose of this study was to jointly analyze well data, seismic data and CSEM data to provide a clear appraisal of a prospect offshore West Africa. Firstly, CSEM data was modeled and inverted. Results were then integrated with the available seismic and well data in order to better understand the resistivity changes we were seeing in the CSEM inversion. In particular, the observation of a low resistivity zone coincident with the seismically mapped prospect is disappointing; however two plausible geological explanations were considered and led to the decision of dropping the block.

Inversion of controlled-source electromagnetic data is dealt with for a geophysical application. The goal is to retrieve a map of conductivity of an unknown body embedded in a layered underground from measurements of the scattered electric field that results from its interaction with a known interrogating wave. This constitutes an inverse scattering problem whose associated forward problem is described by means of electric field domain integral equations. The inverse problem is solved in a Bayesian framework in which prior information is introduced via a Gauss-Markov-Potts model. This model describes the body as being composed of a finite number of different materials distributed into compact homogeneous regions. The posterior distribution of the unknowns is approached by means of the variational Bayesian approximation as a separable distribution that minimizes the Kullback-Leibler divergence with respect to the posterior law. Thus, we get a parametric model for the distributions of the induced currents, the conductivity contrast, and the various parameters of the prior model that are obtained following a semisupervised iterative approach. This method is applied to multifrequency synthetic data corresponding to a 3D crosswell configuration in which the sought body is made of two separated anomalies, a conductive heterogeneity and a resistive one, and its results are compared with that given by the classic contrast source inversion (CSI). The method succeeds in retrieving compact homogeneous regions that correspond to the two anomalies whose shape and conductivities are obtained with a good precision compared with that obtained with CSI.

A sequential inversion methodology for combining geophysical data types of different resolutions is developed and applied to monitoring of large-scale CO2 injection. The methodology is a two-step approach within the Bayesian framework where lower resolution data are inverted first, and subsequently used in the generation of the prior model for inversion of the higher resolution data. For the application of CO2 monitoring, the first step is done with either controlled source electromagnetic (CSEM) or gravimetric data, while the second step is done with seismic amplitude-versus-offset (AVO) data. The Bayesian inverse problems are solved by sampling the posterior probability distributions using either the ensemble Kalman filter or ensemble smoother with multiple data assimilation. A model-based parameterization is used to represent the unknown geophysical parameters: electric conductivity, density, and seismic velocity. The parameterization is well suited for identification of CO2 plume location and variation of geophysical parameters within the regions corresponding to inside and outside of the plume. The inversion methodology is applied to a synthetic monitoring test case where geophysical data are made from fluid-flow simulation of large-scale CO2 sequestration in the Skade formation. The numerical experiments show that seismic AVO inversion results are improved with the sequential inversion methodology using prior information from either CSEM or gravimetric inversion.

Numerous publications have dealt with estimations of resistivity from elastic parameters and vice versa. Attempts have been made in the cross-property relationship of elastic and electric properties, in particular, velocity to resistivity using different parameters, such as porosity and water saturation. These types of transforms are currently used to predict background seismic velocities and resistivities, or even start models for seismic or controlled source electromagnetic (CSEM) inversions. However, they are not reliable predictors because they depict the regional elastic or electric variations with limited accuracy. We present a novel approach for the development of models capable of estimating the regional subsurface resistivity based on information from regional wells and seismic inversions. We apply multivariate nonlinear regression on data derived from regional wells and seismic inversions and subsequently produced an estimation of subsurface horizontal resistivity that could be either used as a direct hydrocarbon indicator or provide a constraint on the horizontal resistivity in anisotropic CSEM inversions. We have verified the validity of the approach using two data sets from the Norwegian continental shelf. We found very good agreement between the borehole-measured and predicted resistivity.

Gas hydrates are a potential energy resource and hazard for drilling and infrastructure, yet estimates of global volume vary by over three orders of magnitude. Hydrates are electrically resistive compared to water saturated sediment and so electromagnetic methods provide an additional tool to seismic surveys and drilling for determining hydrate saturations. A marine electromagnetic survey was carried out at Hydrate Ridge, Oregon, USA, with the aim of testing the use of controlled source electromagnetic (CSEM) and magnetotelluric (MT) methods to map gas hydrate and free gas below the gas hydrate stability zone. A 2-D CSEM inversion supports the scenario deduced from previous seismic and drilling results, which indicate two mechanisms of hydrate emplacement: a transport-dominated and reaction-dominated regime. A prominent resistive region of 2.5–4 ?m at a depth of about 130 mbsf, near the seismic bottom simulating reflector (BSR), suggests that 27 to 46 per cent of the bulk volume is filled with hydrate, depending on whether Archie's Law or the Hashin-Strikman bounds are used. This is representative of a reaction-dominated regime for hydrate emplacement, and where a significant low velocity zone exists based on a seismic tomography inversion, suggests large quantities of free gas below the BSR. Electrical resistivity logging while drilling (LWD) data show general agreement with the CSEM inversion model except for a CSEM-derived resistive region at seismic horizon A, known to transport free gas into the gas hydrate stability zone. Inversion of MT data collected simultaneously during the CSEM survey provides a complimentary low-resolution image of the shallow sediments and shows folding in the accretionary complex sediments similar to that imaged by a tomographic seismic velocity model.

Survey data of marine controlled source electromagnetic (CSEM) geophysical surveys is not able to proceed far without numerical modeling. Finite Difference (FD) and Finite element (FE) numerical methods are the most used techniques in geophysical modeling. These methods are reliable for complex structural media; however the computational cost is very high. The computational cost, accuracy and efficiency are reliant on sophisticated mesh structure. This paper discusses the orthogonal wavelet basis functions that give a natural framework to adapt spatial grids to localize the solution in spatial and time domain. Modeling for proper mesh structure is achieved by using wavelet basis functions called wavelet optimized finite difference (WOFD) method. In WOFD method, wavelet transform is used to determine where to coarsen/refine the grid. As a resultant, solution region will become with irregular grid point. This method will add grid points where solution is erratic and sparse where solution is smooth. Now the solution can be obtained with better accuracy and less computational cost by using finite number of terms. The efficiency of this method is assessed in terms of accuracy; computational cost and number of mesh grids for different 1D heterogeneous media. WOFD method provides new flexible numerical tool for marine CSEM geophysical modeling as discretization to local media properties. This flexibility is important and could be invaluable when the solution region is very complex.

libEMMI_MGFD: A program of marine controlled-source electromagnetic modelling and inversion using frequency-domain multigrid solver

ABSTRACTA framework is proposed to bridge coarse and fine meshes in a single simulation within the phase field method for fracture. Fine meshes are used in the vicinity of localized defects to accurately capture crack initiation, while coarse meshes are used away from initial defects and include only crack propagation paths. This reduces the prohibitive computational times associated with uniformly fine meshes over the entire domain, or with the use of complex adaptive meshes in the phase field method. The coupling between the two overlapping meshes is achieved using a variational formulation in which the energies of the models associated with the fine and coarse meshes are weighted in the superposition zone. Two situations are considered. The first includes the resolution of the phase field problem only in the fine mesh, while the coarse mesh is limited to the undamaged elastic problem. In the second situation, cracks can propagate in both the fine and coarse mesh. Variational formulations and associated finite element implementations are detailed. Numerical examples are presented, showing the potential of this approach to significantly reduce computational costs in the phase field method for cracking without affecting the accuracy.

The controlled-source electromagnetic (CSEM) and magnetotelluric method (MT) are two techniques that can be jointly used to explore the resistivity structure of the earth. Such methods have, in recent years, been applied in marine environments to the exploration and appraisal of hydrocarbons. In many situations the electric properties of the earth are anisotropic, with differences between resistivity in the vertical direction typically much higher than those in the horizontal direction. In cases such as this, the two modes of the time-harmonic electromagnetic field are altered in different ways, implying that the sensitivity to the earth resistivity may vary significantly from one particular resistivity component (scalar, horizontal or vertical) to another, depending on the measurement configuration (range, azimuth, frequency or water depth). In this paper, we examine the sensitivity of the electromagnetic field to a vertically anisotropic earth for a typical set of configurations, compare inversion results of synthetic data characterizing a vertically anisotropic earth obtained using the isotropic and anisotropic assumptions and show that correctly accounting for anisotropy can prevent artefacts in inversion results.

We present results from an investigation into 1D inversion of controlled-source electromagnetic (CSEM) data. Based on inspection of a data set, we formulate a simple empirical noise model described by a few pragmatically determined parameters. We also investigate the effects of transmitter height above the seafloor and include the data uncertainty resulting from varying transmitter height in our noise model. Based on the noise model and assumptions about the available data, we analyze model parameter uncertainty estimates derived from the a posteriori model covariance matrix for a resistive layer buried at depth. We find that the layer parameters uncertainty primarily depends on the depth of burial and the thickness of the layer. We then formulate quantitative bounds for these parameters, within which we have a small uncertainty of the parameters of the resistive layer. The depth of burial and the transverse resistance of the layer become better determined the higher its resistance. We invert a field data set with multilayer and four-layer models and find a resistive layer at a depth of 1500–1600m below the seafloor. Seismic results from the area indicate a depth of 2000m.

SUMMARY Carbon capture and storage (CCS) within sealed geological formations is an essential strategy to reduce global greenhouse gas emissions, the primary goal of the 2015 United Nations Paris Agreement. Large-scale commercial development of geological CO2 storage requires high-resolution remote sensing methods to monitor CO2 migration during/after injection. A geological formation containing a CO2 phase in its pore space commonly exhibits higher electrical resistivity than brine-saturated (background) sediments. Here, we explore the added value of the marine controlled-source electromagnetic (CSEM) method as an additional and relevant geophysical tool to monitor moderate to significant changes in CO2 saturation within a fluid conduit breaking through the seal of a CCS injection reservoir, using a suite of synthetic studies. Our 2-D CSEM synthetic models simulate various geological scenarios incorporating the main structural features and stratigraphy of two North Sea sites, the Scanner Pockmark and the Sleipner CCS site. Our results show significant differentiation of leakage through the seal with CO2 saturation ($S_{{\rm CO}_2}$) ranging between 20 and 50 per cent, while our rock physics model predicts that detection below 20 per cent would be challenging for CSEM alone. However, we are able to detect with our 2-D inversion models the effects of saturation with 10 and 20 per cent CO2 within a chimney with 10 per cent porosity. We demonstrate that simultaneous inversion of Ey and Ez synthetic electric field data facilitates a sharper delineation of a CO2 saturated chimney structure within the seal, whereas Ez synthetic data present higher sensitivity than Ey to $S_{{\rm CO}_2}$ variation, demonstrating the importance of acquiring the full 3-D electric field. This study illustrates the value of incorporating CSEM into measurement, monitoring and verification strategies for optimal operation of marine CCS sites.