Towed Streamer Electromagnetic Research Articles

Least Squares Migration of Synthetic Aperture Data for Towed Streamer Electromagnetic Survey

Towed streamer electromagnetic (TSEM) survey is an efficient data acquisition technique capable of collecting a large volume of electromagnetic (EM) data over extensive areas rapidly and economically. The TSEM survey is capable of detecting and characterizing marine hydrocarbon (HC) reservoirs. However, interpretation of the TSEM data is still a very challenging problem. We propose solving this problem by migrating the optimal synthetic aperture (OSA) data for the TSEM survey. We first represent the OSA data as a solution of Lippmann-Schwinger equation and then demonstrate that the migration of OSA data is just the inner product of the backward-propagated and forward-propagated EM fields. The migration problem is solved iteratively within the general framework of the reweighted, regularized, conjugate gradient (RRCG) method. The proposed method was tested with two synthetic models. We also applied this method to the TSEM data set collected in the Barents Sea and revealed a resistive layer at a depth of about 500 m.

Salt Delineation From Electromagnetic Data Using Convolutional Neural Networks

With recent advances in machine learning, convolutional neural networks (CNNs) have been successfully applied in many fields, and several attempts have been made in the field of geophysics. In this letter, we investigated the mapping of subsurface electrical resistivity distributions from electromagnetic (EM) data with CNNs. To begin imaging electrical resistivity using CNNs, we carried out precise delineation of a subsurface salt structure, which is indispensable for identification of offshore hydrocarbon reservoirs, using towed streamer EM data. For training the CNN model, an electrical resistivity model, including a salt body, and corresponding EM data calculated through numerical modeling were used as the label and input, respectively. The optimal weights and biases of the CNN were obtained minimizing the mean-square error between the predicted resistivity distribution and the target label. The final CNN model was selected using a validation data set during training. After training, we applied the trained CNN to test data sets of noisy data and simulated-SEAM data, which were not provided to the network during training. The test results demonstrate that our trained CNN model is stable, reliable, and efficient, and indicate the possibility of successful application of our CNN model to field data. Our study has shown the promising potential of CNNs for identifying defined subsurface electrical resistivity structures that are difficult to find using conventional EM inversion.

Case study: North Sea heavy oil reservoir characterization from integrated analysis of towed-streamer EM and dual-sensor seismic data

Integrated analysis of geophysical data can provide valuable information on reservoir properties upon which exploration, appraisal, and development decisions can be made. Here we derive a geophysical reservoir characterization workflow from quantitative interpretation of towed-streamer electromagnetic (EM) and dual-sensor seismic data. The workflow facilitates the reliable extraction of complementary information from two high-fidelity data sets. We demonstrate how the new workflow enables a robust and reliable integration of towed-streamer EM and seismic data with examples from data acquired in a complex geologic region of the North Sea where the heavy oil fields known as Bressay, Bentley, and Kraken (BBK) are located. The BBK discoveries pose several challenges to EM surveying. Airwave coupling in the relatively shallow ocean significantly complicates the reservoir signals. Further, the reservoirs are in close proximity to other high-resistivity features, such as shallow gas in the overburden, the regional Balder Tuff, and granite intrusions. Seismic imaging over these fields is also challenging due to the presence of injectites with steep and irregular geometries. Furthermore, the heavy oil charge means there is no direct hydrocarbon indication in the seismic data due to the low acoustic impedance contrast between the reservoir and surrounding shale.

Comparison of Detection Capability by the Controlled Source Electromagnetic Method for Hydrocarbon Exploration

Marine controlled-source electromagnetic (CSEM) is an efficient offshore hydrocarbon exploration method that has been developed during the last 18 years. Sea Bed Logging (SBL) and towed streamer electromagnetic (TSEM) are two different data acquisition systems. We compared these two methods by using 1D sensitivity modeling and 2D Occam’s inversion. Based on this research, we tested the effect of frequency, offset range, water depth, reservoir size, and reservoir depth on the detection capability of the two acquisition methods in terms of sensitivity. In order to test the methodology clearly and simply, the geological model was extremely simplified for the inversion. The effect of these parameters on resolution was checked as another purpose. To easily evaluate our inversion results, a simple quantity was employed that we called the anomaly transverse resistance ratio. In the shallow water environment, both the SBL and the TSEM systems had a good sensitivity to the high resistivity targets. However, in the deep water environment, the SBL system had a low noise floor. Then, it could provide better detectability to the deep target. The TSEM had the advantage in terms of the horizontal resolution because of the dense in-line sampling of the electric field.

Rapid Imaging of Towed Streamer EM Data Using the Optimal Synthetic Aperture Method

The mainstream approach to the interpretation of towed streamer electromagnetic (EM) data is based on 2.5-D and/or 3-D inversions of the observed data into the resistivity models of the subsurface formations. However, the rigorous 3-D and even 2.5-D inversions require large amounts of computational power and time. The synthetic aperture (SA) method is one of the key techniques in remote sensing using radio frequency signals. During recent years, this method was also applied to low-frequency EM fields used for geophysical exploration. This letter demonstrates that the concept of the SA EM method can be extended for rapid imaging of the large volumes of towed streamer EM data. We introduce a notion of virtual receivers, which complement the actual receivers in the construction of the SA for the towed streamer data. A numerical study demonstrates that this method increases the EM response from potential subsurface targets and opens a possibility for on-board real-time imaging of EM data during a survey. The method is illustrated by the imaging of towed streamer EM data acquired over the Troll oil and gas fields in the North Sea. Remarkably, the imaging of the entire towed streamer EM survey requires just a few seconds of computation time on a desktop PC. This result is significant, because it opens a possibility for real-time imaging of the towed streamer EM survey data.

Large-scale seismically guided anisotropic inversion of towed-streamer EM data in the Barents Sea

This paper presents a fast and efficient large-scale anisotropic inversion technique for towed streamer electromagnetic (EM) data, which incorporates seismic constraints. The inversion algorithm is based on the 3D contraction integral equation method and utilizes a reweighted regularized conjugate gradient technique to minimize the objective functional (Zhdanov et al. 2014a, b). We have also introduced the concept of a moving sensitivity domain for seismically guided EM inversion, originally developed for airborne EM surveys (Zhdanov and Cox, 2013), which makes it possible to invert the entire large-scale towed streamer EM survey data while keeping the accuracy of the computation of the EM fields. The developed algorithm and software can take into account the constraints based on seismic and well-log data, and provide the inversion guided by these constraints. To demonstrate the practical effectiveness of this approach for large-scale inversion of marine EM data, as well as integration with seismic data, we apply the method to the inversion of about 2000 line-km of towed streamer EM data. The data form part of a larger survey in the Norwegian Barents Sea (McKay et al., 2016). We show that the technique produces a single resistivity model that is consistent with both the measured EM data and the main seismically defined structures. Thus, the resistivity model is ready to be interpreted and used in further quantitative interpretation studies.

Advanced 3D imaging of complex geoelectrical structures using towed streamer EM data over the Mariner field in the North Sea

Towed streamer electromagnetic (EM) data acquired at the Mariner heavy oilfield in the UK sector of the North Sea have been inverted using a fast and efficient 3D anisotropic inversion code. The towed streamer EM system was towed from a single vessel. The system consisted of a horizontal bipole source and electrode sensors housed in a streamer cable. This enabled a densely sampled grid of data over the subsurface volume of interest. The purpose was to estimate the resistivity structure in a volume including the Maureen and Heimdal reservoir structures in the Mariner complex. The 3D inversion algorithm is based on the contraction integral equation method and utilizes a re-weighted regularized conjugate gradient technique to minimize an objective functional (e.g., Zhdanov et al., 2014). A moving sensitivity domain approach is introduced to handle the large amount of data over the large area (Zhdanov, 2010; Zhdanov and Cox, 2012; Zhdanov et al., 2014; Cox and Zhdanov, 2014). This inversion method is proven to be fast and efficient and is here shown to be suitable for towed streamer EM data from complex geological environments such as the Mariner area. In this case, the final 3D resistivity cube after inversion and with a corresponding normalized misfit of 5.4% correlates well with the expected structure from seismic data and well logs. In particular, the 3D inversion was able to extract an anomaly with vertical and horizontal resistivities of 8-10 and 4-5 Ohm-m, respectively, corresponding to the Maureen and Heimdal reservoirs close to the resistive chalk and basement. The run time on a PC cluster was only seven hours for the full 3D inversion with data from all survey lines covering the area of interest.

Anisotropic 3D inversion of towed-streamer electromagnetic data: Case study from the Troll West Oil Province

One of the critical problems in the interpretation of marine controlled-source electromagnetic geophysical data is taking into account the anisotropy of the rock formations. We evaluated a 3D anisotropic inversion method based on the integral equation method. We applied this method to the full 3D anisotropic inversion of towed-streamer electromagnetic (EM) data. The towed-streamer EM system makes it possible to collect EM data with a high production rate and over very large survey areas. At the same time, 3D inversion of towed-streamer EM data has become a very challenging problem because of the huge number of transmitter positions of the moving towed-streamer EM system, and, correspondingly, the huge number of forward and inverse problems needed to be solved for every transmitter position over the large areas of the survey. We overcame this problem by exploiting the fact that a towed-streamer EM system’s sensitivity domain is significantly smaller than the area of the towed-streamer EM survey. This approach makes it possible to invert entire towed-streamer EM surveys with no approximations into high-resolution 3D geoelectrical sea-bottom models. We present an actual case study for the 3D anisotropic inversion of towed-streamer EM data from the Troll field in the North Sea.

Focusing Controlled Sensitivity of Geophysical Data

Different geophysical surveys have a specific sensitivity to geological targets, determined by the physical nature of the observed geophysical field, the design of the data acquisition system, and the configuration and type of the source of the recorded data. The sensitivity is usually limited to some part of the examined geological formation, located relatively close to the sensors. This paper introduces a concept of controlled sensitivity, which enables the sensitivity of a geophysical data to be increased within a specific target area of a geological formation. In particular, this method can be used to increase the sensitivity of the data with the depth. The developed approach is demonstrated with a numerical study of the sensitivity of marine Towed Streamer Electro-Magnetic (TSEM) surveys. However, a general mathematical formulation of the method, presented in this paper, makes it possible to apply the developed technique to a wide variety of geophysical data.

3D inversion of towed streamer EM data: a model study of the Harding field with comparison to CSEM

Michael S. Zhdanov, Chris Anderson, Masashi Endo, Leif H. Cox, Martin Čuma, Glenn A. Wilson, Noel Black and Alexander V. Gribenko provide an early study of the challenges involved in validating offshore electromagnetic (EM) data acquired using a towed streamer receiver (currently under development) and compare the results with existing seabed-based marine controlled source electromagnetic (CSEM) technology.