3D Controlled Source Electromagnetic Data Research Articles

3D inversion of multifrequency controlled-source electromagnetic data and its application to geothermal exploration in the Tianzhen region of the northern Datong Basin, China

Owing to its sensitivity to hydrothermal alteration and geothermal fluids, the distribution of subsurface electrical conductivity provides critical information for characterizing geothermal systems. For geothermal exploration, the controlled-source electromagnetic (CSEM) technique provides a crucial tool to image the subsurface resistivity structures, especially in areas with strong cultural noise. Usually, land-based CSEM surveys are carried out with dozens of operating frequencies to enhance spatial resolution. However, the 3D inversion of multifrequency CSEM data using the commonly used direct solver is challenging with limited computational resources. In this study, we implement a practical inversion strategy for interpreting 3D multifrequency CSEM data. By combining a hybrid direct-iterative solver with the inexact Gauss-Newton optimization, 3D inversion of CSEM data involving multiple frequencies can be performed effectively on typical workstations. First, we test the effectiveness of the developed approach using synthetic multifrequency 3D CSEM data generated for a simplified geothermal model. The inversion strategy is then applied to the multifrequency CSEM field data collected for the geothermal exploration at Tianzhen region in Shanxi Province, China. The comparison between the inversion results using the sparse data set (six frequencies) and the dense data set (12 frequencies) highlights the necessity of using data from more frequencies in the inversion to improve the resolution. The resulting 3D resistivity model clearly delineates the clay alteration layers and shallow thermal reservoirs of the potential high-temperature geothermal system within the study area, while its deep heat source is not revealed owing to the limited investigation depth of the survey.

Exploring geothermal resources using electromagnetic methods in coastal areas of volcanic islands: Challenges of nearshore and land 3D controlled-source electromagnetic data

Three-dimensional geophysical exploration is essential in identifying favorable areas and derisking high-temperature geothermal projects. In particular, electrical resistivity imaging plays a key role in this exploration due to its sensitivity to the presence of alteration products, geothermal fluid circulation, and temperature. As 3D seismic exploration is rarely effective in volcanic environments, resistivity methods such as magnetotellurics (MTs) are often used to extract deep structural information. However, deep electromagnetic (EM) imaging in coastal areas of volcanic islands with MT can be challenging due to anthropogenic noise induced by urbanized areas concentrated around the coast. The use of active EM sources, such as airborne EM (AEM) and controlled-source EM (CSEM), as a complement to MT is a solution for overcoming anthropogenic noise. However, applying these methods in this context is still challenging due to the proximity to the sea/land interface, large variations in topography and nearshore bathymetry, and the heterogeneity of the near surface. Our approach outlines the challenges of acquiring, processing, and inverting nearshore and land 3D CSEM data in such complex environments. The CSEM data are part of a multimethod geothermal exploration on the island of Martinique in the French West Indies, and its 3D inversion result is compared with the previous regional 3D MT and AEM inversion results. In addition to MT, CSEM may highlight the location of a potential high-temperature paleo-reservoir at shallow depths under the urbanized area of Petite-Anse covered by a paleo-clay cap ranging from a few meters to several hundred meters in thickness. We conclude by proposing possible improvements for CSEM and multimethod methodologies to obtain more reliable exploratory models.

Ensemble scenario‐based inversion: A new approach for estimating the uncertainty of resistivity models derived from 3D controlled source electromagnetic data

AbstractNon‐linear inversion of controlled source electromagnetic data is non‐unique. Inversion ambiguity and uncertainty grow with model complexity and limitations in sensitivity, for example when imaging deep targets. Uncertainties should be estimated. The best way to do that is by statistical inversion techniques. Because of the large number of parameters of 3D models, these methods are too costly for 3D applications. But neglecting or underestimating uncertainties often leads to erroneous interpretation and poor exploration decisions. The number of inversion parameters can be dramatically reduced while still being able to describe a complex 3D subsurface. To obtain that, I represent prior information by an input ensemble of geologically reasonable prior models. The model space is defined by the principal directions of this ensemble, where the inversion parameters are the coefficients of the different components. In this model space, inversion becomes much more efficient and can produce an updated ensemble of posterior models at the same computational cost as a controlled‐source electromagnetic inversion project using conventional non‐linear inversion techniques. I present examples where unique Gauss–Newton inversions lead to difficult interpretations and poor conclusions about hydrocarbon presence and saturation. The new approach provides a quantitative estimation of resistivity ambiguities and uncertainties leading to better interpretation and safer decisions. The examples use 2D synthetic controlled‐source electromagnetic data and 3D controlled‐source electromagnetic field data.

Use of structure-guided 3D controlled-source electromagnetic inversion to map karst features in carbonates in offshore northwest Borneo

Fractured and/or karstic carbonates (FKCs) in the subsurface are commonly associated with significant drilling risk or reservoir effectiveness issues. Understanding the distribution of karsts will help avoid drilling into possible voids and also reassess risks associated with reservoir effectiveness. A 2020 3D seismic acquisition in offshore northwest Borneo provided data for identifying new carbonate prospects and an opportunity to revisit a 2010 marine controlled-source electromagnetic (CSEM) survey that was not designed specifically for FKC mapping but can serve to test new inversion capability for imaging karsted carbonate bodies. A 3D CSEM data were used to detect and characterize the nature (i.e., fractured and/or karsted) of carbonate prospects mapped using 3D seismic data. In one approach, structure tensors computed from these seismic data were used to constrain the 3D CSEM inversion on the Azure cloud platform. In another approach, cross gradients between vertical and horizontal resistivities were used as a structural guide obviating the need for seismic data. The resulting anisotropic resistivity models were validated using resistivity logs from a nearby well; the resistivity results matched the well-logs satisfactorily, providing geologic justification to interpret the presence of karst features in the resistivity volumes. Lateral boundary of the carbonate prospects was mapped based on the resistivity characteristic, in seismic- and nonseismic-guided structure-coupled inversion. Resistivity-depth cross section of the area revealed the presence of resistivity discontinuity at the seismic-inferred boundary of the main carbonate prospect. Also, resistivity depth slices of the models clearly demonstrated that the areal distribution of low and high resistive zones can be mapped and useful deductions such as the presence of FKC and basement characteristics can be made using the 3D inversion of the CSEM data.

Extension of the regularization technique to controlled-source electromagnetic modeling in general anisotropic conductivity media

Traditional Krylov subspace methods can be slow for electromagnetic modeling, particularly at lower frequencies. One of the commonly used remedies is to apply the divergence correction iteratively during the solution process, which requires solving an additional divergence correction equation. Alternatively, we have developed an efficient regularization technique to carry out the forward modeling of the anisotropic effect for 3D controlled-source electromagnetic data. Inside this scheme, we explicitly include the gradient of a scaled divergence correction term into the original curl-curl equation for general anisotropic conductivity structure. This inclusion leads to a significantly better-conditioned linear system of equations without changing the solution of the original system and avoids the solution of an additional equation. The correctness of the developed algorithm is examined based on a vertical transverse isotropic layered model with the semianalytical solution available. Then, we use a tilted transverse isotropic ocean canonical reservoir model and a general anisotropic 3D model to investigate the stability and efficiency of the algorithm. Numerical experiments demonstrate that the developed technique is 0.49–2.9 times faster than the standard algorithm at the considered frequencies.

An edge-based finite element method for 3D marine controlled-source electromagnetic forward modeling with a new type of second-order tetrahedral edge element

This paper presents a second order edge-based finite element method based on a new type of second order edge element for numerical modeling of 3D controlled source electromagnetic data in an anisotropic conductive medium. We adopt the anomalous potential field formulation to avoid the effect of sou rce’s singularity. The computational domain was subdivided into unstructured tetrahedral elements. The sparse linear system was solved using the Induced dimensional reduction (IDR(s)) method with an incomplete LU preconditioner. We have applied the developed algorithm to compute a typical MCSEM response over several 3D models, we compare the numerical results from our method and FEM solution based on conventional first and second order element. The results of comparison shown that our algorithm can significantly reduce the computation cost without loss to much accuracy.

FINITE‐ELEMENT MODELING OF 3D MCSEM IN ARBITRARILY ANISOTROPIC MEDIUM USING POTENTIALS ON UNSTRUCTURED GRIDS

AbstractThis paper presents a new algorithm for the three‐dimensional marine controlled source electromagnetic method modeling in arbitrarily anisotropic medium based on unstructured grids and coulomb gauge. In order to avoid the effect of source singularity, we apply the secondary potential formulation for the quasi‐static of Maxwell's equation. Next, solving the finite element equations with IDR(s) iterative algorithm method combined with the incomplete LU decomposition technology. Once the secondary vector and scalar potential is solved, we can use the moving least square method to calculate their spatial derivative and compute the secondary electric and magnetic field. In order to test the finite element method for numerical modeling of 3D controlled source electromagnetic data in an arbitrarily anisotropic conductive medium of this paper, we applied the developed algorithm to compute the typical CSEM response of two 3D models. The modeling results show that the proposed algorithm is feasible and effective; the IDR(s) is competitive with or superior to ILU‐QMR, ILU‐BICGSTAB methods; the proposed algorithm is general and can be applied to EM modeling in borehole and environment geophysics in arbitrarily anisotropic medium.

A low-rank approximation for large-scale 3D controlled-source electromagnetic Gauss-Newton inversion

We have developed an approximation to the Hessian for inversion of 3D controlled source electromagnetic data. Our approach can considerably reduce the numerical complexity in terms of the number of forward solutions as well as the size and complexity of the calculations required to compute the update direction from the Gauss-Newton equation. The approach makes use of “supershots,” in which several source positions are combined for simultaneous-source simulations. The resulting Hessian can be described as a low-rank approximation to the Gauss-Newton Hessian. The structure of the approximate Hessian facilitates a matrix-free direct solver for the Gauss-Newton equation, and the reduced memory complexity allows the use of a large number of unknowns. We studied the crosstalk introduced in the approximation, and we determined how the dissipative nature of marine electromagnetic field propagation reduces the impact of this noise. Inversion results from recent field data demonstrated the numerical and practical feasibility of the approach.

3D CSEM data inversion using Newton and Halley class methods

For the first time in 3D controlled source electromagnetic data inversion, we explore the use of the Newton and the Halley optimization methods, which may show their potential when the cost function has a complex topology. The inversion is formulated as a constrained nonlinear least-squares problem which is solved by iterative optimization. These methods require the derivatives up to second order of the residuals with respect to model parameters. We show how Green's functions determine the high-order derivatives, and develop a diagrammatical representation of the residual derivatives. The Green's functions are efficiently calculated on-the-fly, making use of a finite-difference frequency-domain forward modelling code based on a multi-frontal sparse direct solver. This allow us to build the second-order derivatives of the residuals keeping the memory cost in the same order as in a Gauss–Newton (GN) scheme. Model updates are computed with a trust-region based conjugate-gradient solver which does not require the computation of a stabilizer. We present inversion results for a synthetic survey and compare the GN, Newton, and super-Halley optimization schemes, and consider two different approaches to set the initial trust-region radius. Our analysis shows that the Newton and super-Halley schemes, using the same regularization configuration, add significant information to the inversion so that the convergence is reached by different paths. In our simple resistivity model examples, the convergence speed of the Newton and the super-Halley schemes are either similar or slightly superior with respect to the convergence speed of the GN scheme, close to the minimum of the cost function. Due to the current noise levels and other measurement inaccuracies in geophysical investigations, this advantageous behaviour is at present of low consequence, but may, with the further improvement of geophysical data acquisition, be an argument for more accurate higher-order methods like those applied in this paper.

CSEM as a tool for better exploration decisions: Case studies from the Barents Sea, Norwegian Continental Shelf

After more than 30 years of exploration and more than 100 wells drilled in the Barents Sea, only one field is in production and one is under development. However, recent discoveries made over the last three years have heightened the interest for exploration in the region. Nevertheless, the industry is still facing major challenges in finding commercial volumes of hydrocarbons, despite the fact that numerous wells have encountered shows or minor amounts of gas and oil, proving a working hydrocarbon system in large parts of the area. Since 2008, 3D controlled-source electromagnetic (CSEM) data have been acquired in the Barents Sea, providing additional geophysical information in the last three licensing rounds. In this paper, we showed how CSEM data can help the industry make better decisions in various stages of exploration. CSEM data, being sensitive to hydrocarbon saturation and volume, have the potential to reduce the risk of exploration failures of a prospect by influencing the chance of success and the expected size and volume. To illustrate this, we showed three case examples. (1) How CSEM can support certain play models, and hence, give valuable information in a license application phase as well as in drilling decisions. (2) How CSEM can support decisions to apply or not apply for certain blocks in a licensing round. (3) How CSEM can help prospect ranking and drill-or-drop decisions. All these three cases demonstrate the power of using CSEM as a complementary tool together with seismic data and other geologic information. This paper argues that CSEM data could have provided a correct prediction for all of the wells drilled in the Barents Sea where 3D CSEM data are available, provided there are sufficient sensitivity and 3D inversion results. This in turn proves the value of acquiring CSEM data in addition to seismic.

Reserves estimation methods for prospect evaluation with 3D CSEM data

Daniel Baltar and Friedrich Roth, explain how 3D controlled-source electromagnetic data can reduce volumetric uncertainty in the reserves estimates process of prospect evaluation.

Exploring frontier areas using 2D seismic and 3D CSEM data, as exemplified by multi-client data over the Skrugard and Havis discoveries in the Barents Sea

There is new and growing enthusiasm for hydrocarbon exploration in the Barents Sea after three recent discoveries: Skrugard, Havis, and Norvarg. We demonstrate how using wide-azimuth 3D controlled-source electromagnetic (CSEM) and 2D seismic data together can improve the identification of prospective areas in the region. An interpretation workflow is presented to show how the challenging resistivity background in the Barents Sea is handled. To do this, we introduce a new inversion attribute called the anomalous vertical resistivity. The inversion attribute is co-visualized with 2D seismic data and used to estimate recoverable reserves. The workflow is illustrated on both synthetic and real data for the Skrugard and Havis discoveries. Both discoveries are identified on CSEM maps and by integrating CSEM data with seismic data. In addition, a new lead is identified. We show that CSEM data carries structural information and that the horizontal resistivity trends can be used with 2D seismic data and well logs to interpret the distribution of good-quality sands. Hydrocarbon reserve calculations based on the 3D CSEM data for the Skrugard and Havis discoveries have P50 values consistent with the publicly available reserve estimates. The reserve estimate for the new lead also shows significant potential.

Field appraisal and accurate resource estimation from 3D quantitative interpretation of seismic and CSEM data

The key questions in field appraisal are: What is the hydrocarbon volume, and how are the hydrocarbons distributed in the field? The ability to answer these questions accurately is critical for deciding whether to produce a field and for developing a production plan. Wells drilled during the appraisal phase provide well and flow-test data, which are combined with structural knowledge from seismic surveys to map the extent of the field and generate a reservoir model. The cost for appraising an offshore field can exceed US $100 million, and it is desirable to obtain the information required with fewer wells if possible. Quantitative interpretation of surface geophysical data provides reservoir properties between well locations and can, therefore, significantly reduce appraisal costs. A quantitative analysis of seismic data using well-log information will typically determine reservoir rock porosity. Other important parameters are hydrocarbon saturation, permeability, and net-to-gross ratio. Quantitative interpretation of several reservoir properties using only the seismic data is associated with significant ambiguity. To determine several of these parameters accurately, complementary geophysical data sets with different sensitivity characteristics are needed. Controlled-source electromagnetic (CSEM) data are sensitive to the fluid type and can provide additional information to determine the hydrocarbon saturation more accurately. We have developed a new quantitative interpretation workflow integrating seismic and marine 3D CSEM data for estimating the hydrocarbon volume and obtaining 3D distributions of the hydrocarbon pore volume. A performance test of the workflow has been carried out on the Troll West Oil Province (TWOP) in the Norwegian North Sea (Figures 1 and 2). This article describes our methodology and presents encouraging results.

Imaging CSEM data in the presence of electrical anisotropy

Formation anisotropy should be incorporated into the analysis of controlled-source electromagnetic (CSEM) data because failure to do so can produce serious artifacts in the resulting resistivity images for certain data configurations of interest. This finding is demonstrated in model and case studies. Sensitivity to horizontal resistivity will be strongest in the broadside electric field data where detectors are offset from the tow line. Sensitivity to vertical resistivity is strongest for overflight data where the transmitting antenna passes directly over the detecting antenna. Consequently, consistent treatment of overflight and broadside electric field measurements requires an anisotropic modeling assumption. To produce a consistent resistivity model for such data, we develop and use a 3D CSEM imaging algorithm that treats transverse anisotropy. The algorithm is based on nonlinear conjugate gradients and full wave-equation modeling. It exploits parallel computing systems to effectively treat 3D imaging problems and CSEM data volumes of industrial size. We use it to demonstrate the anisotropic imaging process on model and field data sets from the North Sea and offshore Brazil. We also verify that isotropic imaging of overflight data alone produces an image generally consistent with vertical resistivity. However, superior data fits are obtained when the same overflight data are analyzed assuming an anisotropic resistivity model.

Investigating the exploration potential for 3D CSEM using a calibration survey over the Troll Field

We demonstrate the ability of the controlled source electromagnetic (CSEM) technique to reveal hydrocarbon reservoirs by reinvestigating the North Sea Troll field with a 3D acquisition grid. Unlike previous applications of 2D CSEM surveys over this field, which have shown a large electromagnetic response over the gas province, the focus in this study is on the thinner and smaller oil reservoir. A weak but consistent anomaly enables detection and delineation of the oil zone and reduces the ambiguity associated with traditional 2D lines. This holds true even for a sparse receiver grid where the target is located between the receiver and source lines. The 3D data show the extent of the oil zone and that it is matched to the top reservoir structural high as well as north-south aligned faults. Variation in magnitude of the anomaly is qualitatively in good correlation with resistivity logs at the well locations. This suggests that 3D CSEM data pave the way for exploration use because of its superiority over 2D data in terms of reduced sensitivity to survey layouts.

Massively parallel electrical conductivity imaging of hydrocarbons using the IBM Blue Gene/L supercomputer

Michael Commer, Gregory A Newman, James J. Carazzone, Thomas A. Dickens, Kenneth E. Green, Leslie A. Wahrmund, Dennis E. Willen, and Janet Shiu discuss an experimental solution to the computational requirements of imaging 3D controlled source electromagnetic data using an IBM supercomputer. A version of this paper appeared in the IBM Journal of Research and Development, Vol 52(1/2), 2008.