Regularized focusing inversion of marine CSEM data using minimum vertical‐support stabilizer

Marine controlled-source electromagnetic (MCSEM) surveys become widely used in off-shore petroleum exploration. However, the interpretation of the MCSEM data is a very challenging problem because of the enormous amount of computations required in the case of the multi-transmitter and multi-receiver data acquisition systems used in these surveys. In this paper we present a new approach to the solution of this problem based on the method of electromagnetic migration and holographic imaging.

An extensive marine controlled source electromagnetic (CSEM) data set was collected in the Gulf of Mexico targeting gas hydrate deposits at four geologically distinct areas within water depths that varied from 900 to 3000 m. The Joint Industry Project 2 drilled two of these locations, Green Canyon 955 and Walker Ridge 313, providing ground truth for the CSEM data. A third survey location, Mississippi Canyon 118 (MC118), is a designated hydrate observatory. We collected both traditional ocean bottom electromagnetic receiver data as well as continuous profiling data using a novel towed three-axis electric field receiver. The towed receiver measured data at a fixed offset of 300 m behind the transmitter, while the ocean bottom receivers recorded data over a range of offsets as the transmitter passed by each receiver. We inverted the CSEM data using a newly developed parallel goal-oriented adaptive finite element-modeling algorithm for efficient 2.5D imaging of the CSEM data. 2D inversions from MC118 are consistent with 1D apparent resistivity pseudosections and reveal resistive areas associated with the carbonate/hydrate mound. An extensive conductive region exists below this, associated with conductive brines sourced from a deeper more resistive salt body. Away from the mound the resistivity structure is a fairly uniform and homogeneous. We present new 2D inversions of the CSEM data that consider electrical anisotropy and constrained inversions that leverage structural control using key seismic horizons along the profiles.

After decades of research and development, Marine Controlled Source ElectroMagnetics (MCSEM) has come into the application phase for oil and gas exploration. However, presently 3D modeling of MCSEM is far from practical with simple models and much computing time. Based on a forward modeling study of 3D frequency-domain MCSEM over a complicated target body and its sensitivity analysis, we derive a method which can delineate the edges of the resistive reservoir. We use the second derivative of the magnitude versus offset (MVO) curve to define the resistive reservoir edges. For the air-wave-dominated far field zone, we suggest using the less affected apparent resistivities in order to improve the adaptability of the method.

One of the major problems in the modeling and inversion of marine controlled-source electromagnetic (CSEM) data is related to the need for accurate representation of very complex geoelectrical models typical for marine environment. At the same time, the corresponding forward-modeling algorithms should be powerful and fast enough to be suitable for repeated use in hundreds of iterations of the inversion and for multiple transmitter/receiver positions. To this end, we have developed a novel 3D modeling and inversion approach, which combines the advantages of the finite-difference (FD) and integral-equation (IE) methods. In the framework of this approach, we have solved Maxwell’s equations for anomalous electric fields using the FD approximation on a staggered grid. Once the unknown electric fields in the computation domain of the FD method are computed, the electric and magnetic fields at the receivers are calculated using the IE method with the corresponding Green’s tensor for the background conductivity model. This approach makes it possible to compute the fields at the receivers accurately without the need of very fine FD discretization in the vicinity of the receivers and sources and without the need for numerical differentiation and interpolation. We have also developed an algorithm for 3D inversion based on the hybrid FD-IE method. In the case of the marine CSEM problem with multiple transmitters and receivers, the forward modeling and the Fréchet derivative calculations are very time consuming and require using large memory to store the intermediate results. To overcome those problems, we have applied the moving sensitivity domain approach to our inversion. A case study for the 3D inversion of towed streamer EM data collected by PGS over the Troll field in the North Sea demonstrated the effectiveness of the developed hybrid method.

We present a new formulation of the integral equation (IE) method for models with variable background conductivity. This method overcomes the standard limitation of the conventional IE method related to the use of a horizontally layered background only. The new IE method still employs the Green's functions for a horizontally layered 1‐D model. However, the new method allows us to use an inhomogeneous background with the IE method. The method was carefully tested for modeling the electromagnetic (EM) field for complex structures with known variable background conductivity. It can find wide application in modeling EM data for multiple geological models with some common geoelectrical features. As an example, we consider marine controlled source EM (MCSEM) application for simulating EM response of a petroleum reservoir in the presence of a salt dome structure.

Marine controlled-source electromagnetic (CSEM) method has proved to be a powerful tool and found its increasing applications for offshore resource exploration and tectonic studies. However, bathymetric variations and anisotropic structures encountered in practical measurements have posed challenges for reliable interpretation of marine CSEM data collected in increasingly complex geologic settings. In this study, we present a Finite element (FE) based forward algorithm for simulating 3-D marine CSEM responses in geologic settings characterized with rough bathymetry and electrical anisotropy. Unstructured tetrahedral meshes are employed to permit precise descriptions of arbitrary seafloor topography. After validating the accuracy of the algorithm, we investigate the effects of bathymetric variations and complicated electric anisotropy separately and jointly on marine CSEM responses. Numerical results have demonstrated that both the bathymetry and electrical anisotropy can cause significant distortions on marine CSEM responses, but to different extent. The effects of full electrical anisotropy and bathymetry have to be taken into consideration for reliable interpretations of marine CSEM data in practice.

The marine controlled-source electromagnetic (CSEM) technique is an application of electromagnetic (EM) waves to image the electrical resistivity of the subsurface underneath the seabed. The modeling of marine CSEM is a crucial and time-consuming task due to the complexity of its mathematical equations. Hence, high computational cost is incurred to solve the linear systems, especially for high-dimensional models. Addressing these problems, we propose Gaussian process (GP) calibrated with computer experiment outputs to estimate multi-frequency marine CSEM profiles at various hydrocarbon depths. This methodology utilizes prior information to provide beneficial EM profiles with uncertainty quantification in terms of variance (95% confidence interval). In this paper, prior marine CSEM information was generated through Computer Simulation Technology (CST) software at various observed hydrocarbon depths (250–2750 m with an increment of 250 m each) and different transmission frequencies (0.125, 0.25, and 0.5 Hz). A two-dimensional (2D) forward GP model was developed for every frequency by utilizing the marine CSEM information. From the results, the uncertainty measurement showed that the estimates were close to the mean. For model validation, the calculated root mean square error (RMSE) and coefficient of variation (CV) proved in good agreement between the computer output and the estimated EM profile at unobserved hydrocarbon depths.

ABSTRACTFrequency domain helicopter-borne electromagnetic (FHEM) surveys have been used as an effective tool for the exploration of underground resources for as long as airborne electromagnetics (AEM) has existed. Large FHEM data sets are commonly interpreted with very fast 1D inversion algorithms that often numerically adequately fit the data sets, even though they yield incorrect results near 2D/3D geological structures. The present study aims to compare 1D and 2D inversion algorithms when applied to the reconstruction of geologically complex regions. We have developed a 2D inversion algorithm incorporating the Levenberg–Marquardt least-squares approach regularised through spatial constraints to retrieve 2D electrical resistivity models associated with arbitrary surface topography. The approach uses a 2D finite element frequency domain solution and a tailored triangular meshing algorithm based on the Ruppert’s Delaunay refinement for the forward modelling. We illustrate how rough topographic effects obscure the FHEM response and affect recovered resistivity models through numerical experiments. We also demonstrate the influence of acquisition frequency and resistivity structure on the topographic effect. In the Appendix, we discuss the FHEM footprint concept from a 2D perspective to assess how 2D effects affect and bias 1D inversion results. Complex 2D synthetic scenarios are presented to compare 1D and 2D inversion in various settings. Two field cases from Norway and Iran are presented to show the model improvements with 2D inversion. For the Norwegian case, the 2D FHEM inversion aligns well with a model retrieved from ground-based electrical resistivity tomography. We show the bias imposed on the 2D inversion of the data set from Iran by improper system calibration.

Seabed Logging (SBL), a tool that uses Marine Controlled Source Electromagnetic (CSEM) method to specifically explorer and map conceivable hydrocarbon-bearing prospects. In spite of the fact that the CSEM technique has been utilized by the scholarly community forever three decades. The focal thought of SBL is the controlling of electromagnetic vitality in thin resistive layers inside conductive dregs. Regardless of whether it has been notable for quite a while that electromagnetic signs can engender from a conductive formation to another by means of resistive areas, for example, air or resistive parts of the lithosphere, the application to hydrocarbon investigation has not been created as of not long ago. This may be because of the vulnerability of getting any critical reaction from thin resistive layers, for example, hydrocarbon stores since electromagnetic vitality is profoundly lessened in conductive silt. In this way, amid the early improvement period of the SBL procedure, a scaled research experiment was performed to approve if a thin resistive layer (e.g. hydrocarbons) covered inside conductive media (e.g. dregs) could be remotely recognized by utilizing electric dipoles as sources and receivers. Information from this analysis were well contrasted with a forward modelling code. However, the analysis cant be applied in the stratified media with challenging sediments, oil and sea water is present. This research have presented the consequences of the main scaled SBL analysis by introducing the major contituents of the SBL surveys with respective forward modelling.

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

We develop a new formulation of the integral equation (IE) method for three-dimensional (3D) electromagnetic (EM) field computation in large-scale models with multiple inhomogeneous domains. This problem arises in many practical appli- cations including modeling the EM fields within the complex geoelectrical structures in geophysical exploration. In geophysical applications, it is difficult to describe an earth structure using the horizontally layered background conductivity model, which is required for the efficient implementation of the conventional IE approach. As a re- sult, a large domain of interest with anomalous conductivity distribution needs to be discretized, which complicates the computations. The new method allows us to con- sider multiple inhomogeneous domains, where the conductivity distribution is differ- ent from that of the background, and to use independent discretizations for different domains. This reduces dramatically the computational resources required for large- scale modeling. In addition, using this method, we can analyze the response of each domain separately without an inappropriate use of the superposition principle for the EM field calculations. The method was carefully tested for the modeling the marine controlled-source electromagnetic (MCSEM) fields for complex geoelectric structures with multiple inhomogeneous domains, such as a seafloor with the rough bathymetry, salt domes, and reservoirs. We have also used this technique to investigate the return induction effects from regional geoelectrical structures, e.g., seafloor bathymetry and salt domes, which can distort the EM response from the geophysical exploration target.

3D non-smooth inversion of gravity data by zero order minimum entropy stabilizing functional

In this paper we present a new approach to the interpretation of the marine controlled‐source electromagnetic (MCSEM) data in areas with rough bathymetry. This approach is based on a new formulation of the integral equation EM modeling method in models with inhomogeneous background conductivity. The developed technique allows us to incorporate known geological structures and bathymetry effects in the method of iterative EM migration/holographic imaging and inversion. This approach provides us with the ability to precompute only once the effect of a known geoelectrical structure (e.g., the bathymetry effect) and keep it unchanged during the entire modeling and migration process. The method is illustrated by numerical examples of modeling and inversion of marine CSEM data in areas with rough bathymetry.

<p>We present an improved interpolation scheme for 2.5D marine controlled-source electromagnetic (CSEM) forward modeling problem. As the resistivity contrast between the seawater and seafloor sediment layers is significant, it is usually difficult to compute the EM fields accurately at receivers which are usually located at the seafloor. In this study, a new interpolation scheme at receivers is proposed, in which the interpolation of EM fields at the cell nodes for the whole computational domain to arbitrary receiver locations is discussed in detail. Numerical tests indicate that, our improved interpolation is more accurate for simulating the EM responses at receivers located on the seafloor, compared with the linear or rigorous interpolation.</p>

An extensive magnetotelluric (MT) survey comprised of 85 sites has been acquired over the Darajat geothermal field in Indonesia to map the geothermal reservoir and the overlying clay cap. The rouged topography and the geometry of the margin of the clay cap makes the resistivity structure 3D at reservoir depth. Although 3D MT inversion is now commonly used in geothermal interpretations 1D and 2D MT inversions are still effective tools for a variety of tasks such as quality assurance. Lower dimensional inversion can also play two critical roles in determining and assessing the resistivity model derived by 3D inversion: 1) by providing a good starting model to reduce the computational cost of the 3D inversion, and 2) by providing a computationally feasible path to stochastic inversion of the data that provides realistic parameter’s standard deviations for use in assessing reliability of the resistivity model. Using a spatially constrained 1D stochastic inversion of the MT data, we investigate the common claim that 1D inversion can provide a pseudo 3D model which closely matches the 3D inversion for the overburden and clay cap layers. The discrepancy between the pseudo 3D and true 3D inverse models increases with depth, however the presence of the core resistive feature of the field is still indicated at approximately the same depth as found in the true 3D model. Analysis of the 1D model parameter probability density functions shows that layer thicknesses are better determined than layer resistivities.