Controlled-Source Electromagnetic Approaches for Hydrocarbon Exploration and Monitoring on Land

Streich, Rita

doi:10.1007/s10712-015-9336-0

Cited by 143 publications

(54 citation statements)

References 210 publications

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“…As prospecting for new resources has moved into geologically complex areas, the value of integrating different types of data has been recognized by the industry and significant investments have been made to develop integration platforms (e.g., DellAversana et al 2016) and sponsor case studies in order to gain the necessary experience (e.g., Colombo et al 2010;Chen and Hoversten 2012;Moorkamp et al 2011;Roberts et al 2016). In addition, the importance of so-called nonseismic techniques in the exploration workflow has increased over the last fifteen years (Constable 2010;MacGregor and Tomlinson 2014;Strack 2014;Streich 2016). In this case, the focus of the study is on the Santos Basin, offshore Brazil, and to which extent integrating seismic, magnetotelluric, gravity and magnetic data can help to constrain the geometry of salt and carbonate units.…”

Section: Joint Inversion With Structural Constraintsmentioning

confidence: 99%

Integrating Electromagnetic Data with Other Geophysical Observations for Enhanced Imaging of the Earth: A Tutorial and Review

Moorkamp

2017

Surv Geophys

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In this review, I discuss the basic principles of joint inversion and constrained inversion approaches and show a few instructive examples of applications of these approaches in the literature. Starting with some basic definitions of the terms joint inversion and constrained inversion, I use a simple three-layered model as a tutorial example that demonstrates the general properties of joint inversion with different coupling methods. In particular, I investigate to which extent combining different geophysical methods can restrict the set of acceptable models and under which circumstances the results can be biased. Some ideas on how to identify such biased results and how negative results can be interpreted conclude the tutorial part. The case studies in the second part have been selected to highlight specific issues such as choosing an appropriate parameter relationship to couple seismic and electromagnetic data and demonstrate the most commonly used approaches, e.g., the cross-gradient constraint and direct parameter coupling. Throughout the discussion, I try to identify topics for future work. Overall, it appears that integrating electromagnetic data with other observations has reached a level of maturity and is starting to move away from fundamental proof-of-concept studies to answering questions about the structure of the subsurface. With a wide selection of coupling methods suited to different geological scenarios, integrated approaches can be applied on all scales and have the potential to deliver new answers to important geological questions.

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Section: Joint Inversion With Structural Constraintsmentioning

confidence: 99%

Integrating Electromagnetic Data with Other Geophysical Observations for Enhanced Imaging of the Earth: A Tutorial and Review

Moorkamp

2017

Surv Geophys

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“…Over the past decades, transient electromagnetic method (TEM) has become widely used in hydro geophysical investigation [1] , mineral [2] and hydrocarbon exploration [3] . In this procedure, much effort has been made to improve the accuracy of the TEM method to meet the demands of the sensitivity properties of different exploration targets in diverse geological settings.…”

Section: Introductionmentioning

confidence: 99%

The denoising of the TEM response from a PRBS source using Hilbert-Huang transform

Hai¹,

Xue²,

Zhao³

et al. 2016

Proceedings of the 7th International Conference on Environment and Engineering Geophysics &Amp; Summit Forum of Chinese Academy

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Abstract-The denoising process is critical when processing transient electromagnetic (TEM) sounding data. For the full waveform PRBS response, an inadequate noise estimation may result in an erroneous interpretation. We consider the Hilberthuang transform and its application to suppress the noise in the PRBS response. The focus is on the thresholding scheme to weed out the energy corresponding to the noise and the analysis of the signal based on its Hilbert time-frequency representation. The method firstly decomposes the signal into the intrinsic mode function, and then, inspired by the thresholding scheme in wavelet analysis, an adaptive and interval thresholding is conducted to set to zero all the components in intrinsic mode function which are lower than a threshold related to the noise level. The algorithm is based on the characteristic of the PRBS response. The HHT based denoising scheme is tested on the synthetic data and applied to the field data with different noise level. The result shows that the proposed method has a good capability in denoising and detail preservation.

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“…Many studies have shown that controlled-source electromagnetic (CSEM) induction methods have been integrated with seismic methods and have had a well-established place in hydrocarbon exploration for more than half a century, particularly in difficult circumstances such as seismic scattering in subsalt and subbasalt exploration, or for alleviating the increasing risks associated with deep boreholes (Strack and Vozoff 1996;Constable 2006). Both marine and land CSEM exploration becomes less sophisticated and provides a well-resolved problem where the resistivity contrasts between targets and host rocks are large, and targets are more conductive than the host rocks (Duckworth and O'Neill 1989;Streich 2016). This is typically challenging and a significant problem for CSEM in hydrocarbon exploration when imaging resistive reservoirs within a more conductive environment (Kellett and Maris 2002;Vanhala et al 2004;Smith, McConnell and Rowe 2008;Strack and Aziz 2012;Liu et al 2015).…”

mentioning

confidence: 99%

“…CSEM is also capable of defining the petrophysical properties-such as porosity, pore-fluid type, pore connectivity, and fluid saturation-of an associated hydrocarbon setting using the contrasts in the subsurface resistivity (Nekut and Spies 1989;Strack 2014). Nevertheless, numerous physical limitations produce infeasible results where the target is too deep and embedded in complex structures, where it is too small, or where the variation of resistivity is too small to be detected relevant to the method sensitivity, resolution, penetration, hardware, and noise (Streich 2016). Both marine and land CSEM exploration becomes less sophisticated and provides a well-resolved problem where the resistivity contrasts between targets and host rocks are large, and targets are more conductive than the host rocks (Duckworth and O'Neill 1989;Streich 2016).…”

mentioning

confidence: 99%

“…This is typically challenging and a significant problem for CSEM in hydrocarbon exploration when imaging resistive reservoirs within a more conductive environment (Kellett and Maris 2002;Vanhala et al 2004;Smith, McConnell and Rowe 2008;Strack and Aziz 2012;Liu et al 2015). Both marine and land CSEM exploration becomes less sophisticated and provides a well-resolved problem where the resistivity contrasts between targets and host rocks are large, and targets are more conductive than the host rocks (Duckworth and O'Neill 1989;Streich 2016). Nevertheless, numerous physical limitations produce infeasible results where the target is too deep and embedded in complex structures, where it is too small, or where the variation of resistivity is too small to be detected relevant to the method sensitivity, resolution, penetration, hardware, and noise (Streich 2016).…”

mentioning

confidence: 99%

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Illuminating and optimising a three‐dimensional model of an oil shale seam and its volume distribution using the transient electromagnetic induction method, central part of Jordan

Rajab

Tarazi

2017

Geophysical Prospecting

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The oil shale exploration program in Jordan is undertaking great activity in the domain of applied geophysical methods to evaluate bitumen‐bearing rock. In the study area, the bituminous marl or oil shale exhibits a rock type dominated by lithofacies layers composed of chalky limestone, marls, clayey marls, and phosphatic marls. The study aims to present enhancements for oil shale seam detection using progressive interpretation from a one‐dimensional inversion to a three‐dimensional modelling and inversion of ground‐based transient electromagnetic data at an area of stressed geological layers. The geophysical survey combined 58 transient electromagnetic sites to produce geoelectrical structures at different depth slices, and cross sections were used to characterise the horizon of the most likely sites for mining oil shale. The results show valuable information on the thickness of the oil shale seam at 3.7 Ωm, which is correlated to the geoelectrical layer between 2‐ and 4 ms transient time delays, and at depths ranging between 85 and 105 m. The 300 m penetrated depth of the transient electromagnetic soundings allows the resolution of the main geological units at narrow resistivity contrast and the distinction of the main geological structures that constrain the detection of the oil shale seam. This geoelectrical layer at different depth slices illustrates a localised oil shale setting and can be spatially correlated with an area bounded by fold and fault systems. Also, three‐dimensional modelling and inversion for synthetic and experimental data are introduced at the faulted area. The results show the limitations of oil shale imaging at a depth exceeding 130 m, which depends on the near‐surface resistivity layer, the low resistivity contrast of the main lithological units, and the degree of geological detail achieved at a suitable model's misfit value.

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Controlled-Source Electromagnetic Approaches for Hydrocarbon Exploration and Monitoring on Land

Cited by 143 publications

References 210 publications

Integrating Electromagnetic Data with Other Geophysical Observations for Enhanced Imaging of the Earth: A Tutorial and Review

Integrating Electromagnetic Data with Other Geophysical Observations for Enhanced Imaging of the Earth: A Tutorial and Review

The denoising of the TEM response from a PRBS source using Hilbert-Huang transform

Illuminating and optimising a three‐dimensional model of an oil shale seam and its volume distribution using the transient electromagnetic induction method, central part of Jordan

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