Oil field reservoir characterization and monitoring using electromagnetic geophysical techniques

Wilt, Michael; Alumbaugh, David

doi:10.1016/s0920-4105(03)00041-x

Cited by 29 publications

(14 citation statements)

References 12 publications

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“…al. [4], [5], Marsala et. al., [6] conducted trial experiments in the Haradh field in Saudi Arabia to map the fluid distribution and monitor the movement of injected water, achieving high quality EM data for even large well separations of more than 850 m. With the advances in crosswell electromagnetic imaging, there has also been the need to improve processing and interpretation of the data.…”

Section: Introductionmentioning

confidence: 98%

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

2014

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Technology has fundamentally changed the oil and gas industry enabling it to extract substantial amounts of unconventional resources such as shale gas that were previously non-recoverable or uneconomical to extract. With the development and acquisition of 4D seismic data, engineers have been able to more accurately map out accurately the evolution of fluids within the reservoirs. However, they have encountered the challenge to distinguish between hydrocarbons and injected fluids. Electromagnetic methods have attracted in the last decade substantial interest to exploit the sharp resistivity contrast between hydrocarbons and water, enabling it to track water fluid fronts, optimize injection, thus improving production rates. Conventional approaches to incorporate electromagnetic data into history matching processes have been to invert these data for reservoir parameters and apply those as constraints in the matching process. This approach faces however the challenge that the computational resources required for the inversion may be significant in addition to the requirement for manual postprocessing to ensure meaningful interpretation. In this work we present a novel approach for incorporating a full wave electromagnetic time domain solver in which electromagnetic data are directly included in the history matching process. The full wave modeling enables higher accuracy representation of the underlying structures and its inclusions returns significantly better matchings and forecasts. Introduction Reservoir management has become a quintessential element for coping with the ever increasing demand of emerging countries such as China, Brazil and India and the increasingly more cost-intensive and complex extraction of oil and gas from newly discovered reservoirs. The later development is illustrated in the deep-sea explorations in the Gulf of Mexico and Artic that has pushed technology to the limits and necessitates the increase of recovery rates beyond the current rate of 30 %. Understanding the movement of injected water and hydrocarbons within the reservoir via simulations incorporating field data has been key for increasing recovery rates. Electromagnetic techniques have attracted in the last decade significant attention in the oil and gas industry for its ability to overcome some of the shortcomings of seismic techniques (such as mapping of reservoirs beneath salt layers), and also because it is applicable in areas where governmental regulations forbid the employment of seismic equipment [1], [2]. While resistivity well logging has long been a standard method for determining hydrocarbon reservoirs when drilling for oil, controlled-source electromagnetic methods and crosswell electromagnetic tomography have been at the forefront of the advancement of electromagnetic techniques following the increasing computational resources and advances in technology. Controlled source electromagnetic (CSEM) [3] surveying arose from academic studies of the oceanic lithosphere in the 1980s but has initially attracted limited...

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Section: Introductionmentioning

confidence: 98%

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

2014

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“…1. Focusing on overcoming the poor distinguishability between hydrocarbons and water, EM methods, such as crosswell EM tomography (Wilt and Alumbaugh 2003;Schlumberger Imaging Services Report 2009) and controlled source electromagnetics (CSEM) (Constable and Srnka 2007;Andréis and MacGregor 2008;Strack 2014), attracted attention because of the sharp contrast in conductivity between different fluids (Hu et al 2009) (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

2016

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SummaryIncreasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. Historymatching enhancements (in terms of reduction in the historymatching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25% better compared with a standard history matching with only production data.

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“…Electromagnetic techniques, such as crosswell electromagnetic tomography (Wilt et al, 1995;Wilt and Alumbaugh, 2003) and controlled source electromagnetics (CSEM) (Andréis and MacGregor, 2007;Constable and Srnka, 2007), have recently enabled engineers to overcome the shortcomings of seismic of accurately distinguishing between water and hydrocarbons (Hu et al, 2009), as illustrated in Fig. 1.…”

Section: Introductionmentioning

confidence: 99%

“…1. Crosswell electromagnetic tomography were introduced in the early 1990s to overcome the lack of sensitivity and improve interwell mapping (Wilt and Alumbaugh, 2003). DePavia et al (2008) presented an overview of the progress that has been made in imaging via EM technology and Marsala et al (2008) showed the ability of crosswell induction tomography to achieve accurate resolution for interwells even spaced more than 1 km apart.…”

Section: Introductionmentioning

confidence: 99%

EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

Katterbauer

Hoteit

Sun

2014

Journal of Petroleum Science and Engineering

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Oil field reservoir characterization and monitoring using electromagnetic geophysical techniques

Cited by 29 publications

References 12 publications

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

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