Mapping Hydrocarbons by Integrating Seismic With Electromagnetic and Gravity Attributes

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.

It is well known that no single geophysical method can provide a completepicture of the earth and its properties and recently integrated interpretationand joint inversion of multiple data types has become a much studied topic(Chen et al, 2007; Harris et al, 2009; Jegen et al, 2009; de Stephano et al,2011). The seismic method is in many situations the tool of choice: it isgeneral and widely applicable, and can provide detailed images of sub-surfacestructure and stratigraphy from which complex geological models can beconstructed. If seismic methods can provide the answer to the question ofinterest then this is undoubtedly the tool to use. However although seismicdata are extremely sensitive to the changes in lithology occurring at theboundaries between geological units, they are less sensitive to fluid changeswithin these units. This is because acoustic and elastic properties of theearth show only small changes when the fluid content or saturation is changed. These changes can in some circumstances be detected and used to provideinformation on fluid distribution. In other situations this is difficult orimpossible to do with certainty, and complementary geophysical methods must beemployed to meet the reservoir characterization goal. In many situations electrical resistivity is driven by the properties anddistribution of fluids in the earth. Commercial hydrocarbon deposits may bemany times more resistive than surrounding lithologies. This change inresistivity caused by variations in fluid content and saturation can, inprinciple, be detected using CSEM tools (See Constable & Srnka 2007 for areview of CSEM technology). However when only CSEM data are considered, structural resolution is poor because of the diffusive nature of the EM fields, and the results can be ambiguous because the effect of an increase in porefluid resistivity cannot be distinguished from the effect of a decrease inporosity. The presence of frustrating resistors in the section (for exampletight carbonates, cemented sandstones or volcanics) can also complicate theinterpretation. Well-log data provide a range of measurements, including both resistivity andacoustic/elastic properties as well as a range of further properties. Apetrophysicist analyzing this well log data will take all of these measurementsand integrate them together to provide an interpretation of the lithology andfluid properties. The resistivity measurement in particular provides keyinformation on the fluid content at the well bore. However such informationcannot provide any constraint on the variation of properties away from thewell, across a reservoir. For any given geophysical question, the most robust answer will be obtained byusing the tool, or combination of tools best suited to the task, andintegrating the resulting data within a rock physics framework, to provide ashared earth model that is geologically reasonable, and consistent with each ofthe geophysical data types available. Careful integration of multiple datatypes can allow the strengths in one method to compensate for the weaknesses inanother. Here we consider three data types: seismic, controlled source electromagnetic(CSEM), and well log data. The workflow applied is shown in figure 1. CSEM dataare first inverted to provide a measure of resistivity. Because of the poorstructural resolution of CSEM data taken in isolation, this inversion isconditioned with seismic structural information. From the results, thetransverse resistance (the vertically integrated resistivity), which is wellconstrained by the CSEM method, can be calculated within the intervals ofinterest.

Michael S. Zhdanov, Evgeny P. Velikhov, Martin Čuma, Glenn Wilson, Noel Black and Alexander Gribenko argue that the key to deriving a reliable quantitative interpretationfrom marine controlled-source electromagnetic (CSEM) data is through the integration of shared earth modelling and robust 3D CSEM inversion. An iterative migration method for CSEM data is presented that is equivalent to rigorous inversion, illustrated with a case study of the Shtokman gas field in the Barents Sea.

Summary In this paper, we present a joint inversion approach of the transmitter navigation and the seafloor resistivity for the marine controlled-source electromagnetic (CSEM) data. The approach utilizes the modified BFGS method and the minimum gradient support penalty. An eigenparameter statistical analysis shows that the seafloor resistivity structure and the transmitter navigation parameters (including transmitter azimuth, dip, and horizontal positions) can be independently resolved. The synthetic inversion tests demonstrate that the joint inversion method is able to reconstruct the seafloor resistivity and the orientation and horizontal positions of transmitter antennas.

We present a new method to estimate receiver orientation angle from electric and magnetic data measured during a controlled source electromagnetic (CSEM) survey. By combining field responses at a receiver for pairs of equidistant source-receiver offsets,

SUMMARY Modelling marine controlled-source electromagnetic (CSEM) responses in the fictitious time domain is a novel approach, which facilitates the full exploration of EM diffusive properties in the fictitious wave domain (FWD). Concepts, such as reflections, refractions, diffractions and transmissions, which are used for the analysis of elastic wave propagation can thus be adopted in FWD for interpreting CSEM data. In this paper, we use a high-order finite difference time domain (FDTD) algorithm for modelling marine CSEM responses in both the fictitious time domain and the diffusive frequency domain. A complex frequency shifted perfectly matched layer (CFS–PML) boundary condition is adopted to the FDTD modelling. We demonstrate the performance of the CFS–PML boundary condition and validate the high-order FDTD code in the FWD with the half-space sea water model and in the frequency domain with the 1-D canonical reservoir model. We investigate and analyse the propagation characteristics of electromagnetic fields in the FWD, where we apply wave propagation concepts to interpret marine CSEM data. Similarities between wave and field propagations relevant for marine CSEM data are demonstrated through several 1-D to 3-D numerical examples.

This paper presents an anisotropic 3D inversion algorithm for marine controlled-source electromagnetic (CSEM) data with the assumption that electrical anisotropy is represented by the vertical and horizontal resistivities. For such anisotropic media, the horizontal and vertical electric fields are related to the horizontal and vertical resistivities, respectively. In addition, the horizontal electric field is insensitive to thin, horizontal resistors associated with hydrocarbon reservoirs. Thus, the horizontal electric field contributes mainly to defining the horizontal resistivity of the background media, but not to resolving thin horizontal resistors. As a result, the resolution of marine CSEM data to reservoirs is lower in anisotropic media than for the isotropic case, unless some possible relation between the two resistivities is accounted for in anisotropic inversion. Synthetic examples show that imposing the equality of the two resistivities is important in stabilizing the inversion process and improving the resolution of the reservoir. It is also shown that the reservoir at a depth of 3 km below the seafloor can be well delineated from three-frequencies (0.1, 0.3, and 0.5 Hz) data in deep water (1 km deep), while additional lower frequency (0.05 Hz) data are required to detect the same reservoir in shallow water (100 m deep).

Offshore energy-transition activities typically require the construction of new subsurface facilities where overburden heterogeneity and deformation patterns may not be fully understood. Anisotropic marine controlled-source electromagnetic (CSEM) and seismic refraction imaging can be adapted to geohazard assessments of the overburden to mitigate safety and cost risks in such areas. This is investigated using an area in deepwater northwest Borneo as the case study. For this proof-of-concept study, a well-established multiphysics joint inversion code is extended to handle marine seismic refraction data from conventional towed streamers. Realistic field-scale synthetic models with anomalous resistivities and velocities in the shallow section (approximately 400 m below mudline) are built and their CSEM and seismic refraction responses are first inverted separately and then jointly in three dimensions using the cross-gradient method. The joint inversion recovers the anomalous bodies better than the separate inversions. The velocity model from the joint inversion indicates improvement from the separate inversion but requires a good starting model. As a further test of the methodology, first-break traveltimes are picked from legacy 3D seismic data and inverted with the available sparse CSEM data. For model verification, resistivity and velocity profiles from separate and joint inversion models are extracted at a well location in the survey area and compared with actual well logs. The joint inversion models match the well logs better than the separate inversion models. Moreover, known geohazards (complex fault sets and lateral inflows) from independent geomatics study are imaged in the joint inversion models. In addition, the resistivity anisotropy ratio tracks anomalous zones that correspond to areas of recent complex faulting and potential lateral inflows in the overburden mass transport systems. Thus, the joint inversion of CSEM and seismic refraction data has the potential to improve the mapping of overburden hazards offshore, with the associated resistivity anisotropy serving as a proxy for active ground deformation.

In order to suppress the airwave noise in marine controlled-source electromagnetic (CSEM) data, we propose a 3D deconvolution (3DD) interferometry method with a synthetic aperture source and obtain the relative anomaly coefficient (RAC) of the EM field reflection responses to show the degree for suppressing the airwave. We analyze the potential of the proposed method for suppressing the airwave, and compare the proposed method with traditional methods in their effectiveness. A method to select synthetic source length is derived and the effect of the water depth on RAC is examined via numerical simulations. The results suggest that 3DD interferometry method with a synthetic source can effectively suppress the airwave and enhance the potential of marine CSEM to hydrocarbon exploration.

A scaled experiment for the verification of the SeaBed Logging method

We consider a simple one dimensional marine gas sand model: a reservoir sand layer is buried in an encasing shale host. Using well established petrophysical relationships such as Archie’s law and Gassman’s equations, we create corresponding geophysical models of resistivity, density, P-wave velocity and S-wave velocity. From these models we calculate synthetic frequency domain marine controlled-source electromagnetic (CSEM) data and amplitude vs. angle (AVA) traces to examine a petrophysically coupled method for joint inversion. We then analyze the resolution properties of a joint inversion problem where not only the thickness of the gas layer, the gas saturation and the sandstone porosity are unknown, but several rock physics parameters are as well. Results show that in certain cases, gas saturation and thickness can be independently resolved with a joint inversion. However, the sandstone porosity may be intercorrelated with the bulk and shear moduli of the sand. This result is one of many different outcomes and shall examine a variety of rock physics and reservoir models in our talk.

Exploration of hydrocarbons in the sea is particularly expensive because it is best done by supplying a transmitter with a strong current, which is hazardous to the lives of marine life. A steady supply of voltage and current to the transmitter is normally used to determine the strength of electromagnetic waves. The mineral deposition has been detected using different techniques, both offshore and onshore. Detection of minerals by employing a controlled source electromagnetics (CSEM) has recently proved to be extremely effective with yielding promising results. Due to noise, both the transmitted and received signals may differ. The signal received from the subsurface in marine settings is generally limited by a variety of noise. The frequency spectrum of frequency signals and wave-forms change when they interact with physical objects. Understanding how the frequency spectrum is altered allows us to examine how the signal and wave-forms change. To accurately evaluate and eradicate these noises, they must be researched and taken into consideration. One of the most challenging problems employing Marine CSEM (MCSEM) in the detection of hydrocarbon is airwaves. When an electromagnetic (EM) is passed over a conductive surface, the affected signal is frequently influenced by the resistive body with high resistivity distribution. The signal is recorded by some electromagnetic (EM) fields scattered by subsurface with electric and magnetic sensors. Furthermore, the signal recorded is noise, often known as airwaves. This, however, occurs in shallow water. Hence, this work proposes to use Fast Fourier Transform (FFT) to detect and remove the noise from the transmitted signal to reduce misinterpretation in the exploration of hydrocarbon in shallow water environments. Moreover, the simulated results obtained from the CST EM studio shows that when an EM signal is subjected to FFT, airwaves can be detected and removed, which enhances and reduces the uncertainty in the deposition of the hydrocarbon layer in a shallow water environment.

SUMMARY Efficient simulation of controlled-source electromagnetic methods in complex geological settings is critical for accurate subsurface imaging and resource evaluation. This study presents an advanced adaptive finite element algorithm leveraging non-conforming arbitrary hexahedral meshes and combining the flexibility of adaptive refinement with the accuracy of high-order basis functions to solve challenges in electromagnetic field modelling. We present a high-order finite element algorithm for electromagnetic geophysics that supports adaptive refinement on arbitrary hexahedral meshes, a capability not commonly available in existing implementations. The proposed algorithm resolves sign conflict issues inherent in non-conforming meshes by employing global vertex indices and adjusting constraint matrices, ensuring the tangential continuity of the electromagnetic field across the computational domain. Adaptive refinement is guided by goal-oriented error estimation, enabling precise solving for the electromagnetic response while maintaining computational efficiency. Numerical examples validate the algorithm’s accuracy and performance. In a steel-cased well model, the computational accuracy of our algorithm is verified by comparison with the 3-D cylindrically symmetric algorithm of the open-source software SimPEG. Furthermore, it is demonstrated that arbitrary hexahedral meshes can achieve accurate modelling of the steel casing with a reduced mesh count. The application to the Vallès Basin model demonstrates substantial computational savings using arbitrary hexahedral meshes compared to tetrahedral meshes. Finally, the algorithm successfully models a large-scale oil-gas reservoir, illustrating its robustness in addressing complex geological scenarios and its potential for monitoring dynamic processes such as water intrusion during resource extraction. These results establish the proposed method as a reliable and efficient forward modelling tool for controlled-source electromagnetic applications, providing significant improvement in flexibility, accuracy and computational efficiency.

The effect of seafloor topographic variations on controlled-source electromagnetic (CSEM) responses is investigated using a finite-difference modeling approach for both petroleum and gas-hydrate exploration scenarios. In a deepwater reservoir model, distortions in the inline electric field responses are mainly due to galvanic effects, particularly at long transmitter-receiver (Tx-Rx) offsets, and are characterized by persistent short-wavelength anomalies at all Tx-Rx offsets in the amplitude profiles. In a shallow-water reservoir model, the contribution of inductive effects to bathymetric distortions is large at short Tx-Rx offsets compared to the deepwater case, whereas at long offsets, the distortion pattern is mainly determined by the source-receiver geometry relative to the sea surface because of the airwave effect rather than by the resistivity variations associated with the seafloor topography. A simple correction technique, which is an extension of the topographic correction procedure for magnetotelluric data, is effective in removing the bathymetric distortions for the deep marine case, but cannot be used for the shallow-water case because of the airwave effect. For a gas-hydrate exploration model, it is shown that the bathymetric response can be large enough to mask the target response, because higher frequencies and shorter offsets need to be used to detect the shallow targets. However, the modeling study suggests that the shallow target response can be separated from the bathymetric distortions using the correction method.

SummaryThe marine controlled-source electromagnetic (CSEM) method has been evolving into a geophysical imaging tool for increasingly complex geological settings in which multiple resistive bodies can be resolved. An advanced subsurface imaging workflow for 3D CSEM surveys is presented, which reproduces the resistivity distribution to within a spatial resolution determined by the frequencies included. The performance of our advanced-processing workflow is demonstrated using a case study from the Gulf of Mexico (GOM), where a dense 3D grid was acquired over an area of high-quality seismic data and well log control.At the core of our 3D workflow is an inversion methodology with approximate Hessian-based optimization and a fast finite-difference time-domain forward operator. The optimization matches the synthetic to the measured field within 100–200 iterations and is sufficiently robust in three dimensions to avoid expensive regularization schemes. The sensitivity of the gradient-based inversion to the starting model is addressed by investing considerable effort in building 1D inversion-based starting models. At the same time, 3D inversion algorithms for survey layouts, including azimuthal data, demand high-quality data conditioning for which we present a processing sequence from time-domain electromagnetic data acquired by seabed receivers to frequency-domain data and weights for inversion.Detection and delineation of reservoirs in the presence of salt is recognized as a major challenge to CSEM methods. In order to interpret 3D data accurately in such a complex environment, the true-resistivity cube is built from a sequence of constrained inversion-based interpretation steps. Using a data set acquired in 2008 in the GOM, we demonstrate the ability of our 3D technology to resolve small (2×2 km), low-resistivity pay (Δρ:5Ω·m) targets within the vicinity (< 1 km) of large salt bodies. In this case study, the 3D method converged within 1 week, running on 150 parallel nodes.