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

Katterbauer, Klemens; Hoteit, Ibrahim; Sun, Shuyu

doi:10.1016/j.petrol.2014.07.039

Cited by 21 publications

(12 citation statements)

References 51 publications

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“…Incorporating prior assumptions, the permeability estimates for the reservoir formation exhibited good agreement with the high-permeability features that are deduced from the trend of the faults and fractures in the region (Vasco et al 2008). The integration of InSAR and gravimetric data for history matching purposes follows a similar approach as the integration of seismic and electromagnetic data into history matching as successfully demonstrated by Skjervheim et al (2014), Gosselin et al (2003), and Katterbauer et al (2014b). These difficulties were addressed by Du et al (2010) who employed a micromechanics approach for determining the subsurface properties for two synthetic test cases of the Krechba field (Du et al 2010).…”

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confidence: 54%

“…Despite extensive efforts to employ InSAR data for reservoir characterization, using surface deformation measurements for history matching and reservoir forecasting has been so far limited. The integration of InSAR and gravimetric data for history matching purposes follows a similar approach as the integration of seismic and electromagnetic data into history matching as successfully demonstrated by Skjervheim et al (2014), Gosselin et al (2003), and Katterbauer et al (2014b).…”

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confidence: 98%

“…EnKF techniques have gained momentum in the reservoir community, showing good performances for a variety of history matching problems (Katterbauer et al 2014b(Katterbauer et al , 2015Oliver and Chen 2010;Wang et al 2010;Thulin et al 2007). For reservoir applications, the joint estimation of both dynamic (e.g., pressure and saturation) and static parameters, such as permeability and porosity, poses however a challenge and may require several iterations with the EnKF to ensure sufficiently accurate estimates (Hendricks Franssen and Kinzelbach 2008;Moradkhani et al 2005;Zafari and Reynolds 2005;Wen and Chen 2007).…”

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confidence: 99%

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Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

Katterbauer

Arango

Sun

et al. 2016

Geophysical Prospecting

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Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels and estimating critical reservoir parameters, the sparse spatial nature of this dataset limits the efficiency of the history matching process. Recently, gravimetry techniques have significantly advanced to the point of providing measurement accuracy in the microgal range and consequently can be used for the tracking of gas displacement caused by water influx. While gravity measurements provide information on subsurface density changes, i.e., the composition of the reservoir, these data do only yield marginal information about temporal displacements of oil and inflowing water. We propose to complement gravimetric data with interferometric synthetic aperture radar surface deformation data to exploit the strong pressure deformation relationship for enhancing fluid flow direction forecasts. We have developed an ensemble Kalman‐filter‐based history matching framework for gas, gas condensate, and volatile oil reservoirs, which synergizes time‐lapse gravity and interferometric synthetic aperture radar data for improved reservoir management and reservoir forecasts. Based on a dual state–parameter estimation algorithm separating the estimation of static reservoir parameters from the dynamic reservoir parameters, our numerical experiments demonstrate that history matching gravity measurements allow monitoring the density changes caused by oil–gas phase transition and water influx to determine the saturation levels, whereas the interferometric synthetic aperture radar measurements help to improve the forecasts of hydrocarbon production and water displacement directions. The reservoir estimates resulting from the dual filtering scheme are on average 20%–40% better than those from the joint estimation scheme, but require about a 30% increase in computational cost.

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confidence: 54%

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confidence: 98%

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confidence: 99%

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Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

Katterbauer

Arango

Sun

et al. 2016

Geophysical Prospecting

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“…With the growing availability of time-lapse seismic data for reservoir monitoring purposes, linking these data directly to the dynamics in the reservoir has encountered increasing interest, in particular in history matching [11][12][13][14] . Reservoir history matching has experienced considerable changes in the last decade with data assimilation techniques attracting substantial interest in coping efficiently with the increasing number of parameters that are history matched and the request to quantify efficiently the uncertainty levels in the estimated parameters.…”

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confidence: 99%

A Novel 3D Viscoelastic Acoustic Wave Equation Based Update Method for Reservoir History Matching

Katterbauer¹

2014

International Petroleum Technology Conference

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The oil and gas industry has been revolutionized within the last decade, with horizontal drilling and hydraulic fracturing enabling the extraction of huge amounts of shale gas in areas previously considered impossible and the recovering of hydrocarbons in harsh environments like the arctic or in previously unimaginable depths like the off-shore exploration in the South China sea and Gulf of Mexico. With the development of 4D seismic, engineers and scientists have been enabled to map the evolution of fluid fronts within the reservoir and determine the displacement caused by the injected fluids. This in turn has led to enhanced production strategies, cost reduction and increased profits. Conventional approaches to incorporate seismic data into the history matching process have been to invert these data for constraints that are subsequently employed in the history matching process. This approach makes the incorporation computationally expensive and requires a lot of manual processing for obtaining the correct interpretation due to the potential artifacts that are generated by the generally ill-conditioned inversion problems. I have presented here a novel approach via including the time-lapse cross-well seismic survey data directly into the history matching process. The generated time-lapse seismic data are obtained from the full wave 3D viscoelastic acoustic wave equation. Furthermore an extensive analysis has been performed showing the robustness of the method and enhanced forecastability of the critical reservoir parameters, reducing uncertainties and exhibiting the benefits of a full wave 3D seismic approach. Finally, the improved performance has been statistically confirmed. The improvements illustrate the significant improvements in forecasting that are obtained via readily available seismic data without the need for inversion. This further optimizes oil production in addition to increasing return-on-investment on oil & gas field development projects, especially in offshore environments.

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“…the geological model) from the dynamic fluid flow component, which should provide information to help recovering the geological structures [30,33]. The first successful use of 4D seismic under an EnKF framework was presented by Skjervheim et al in [34] and more recently gained momentum in helping to monitor the fluid flow movement in the reservoir [35,36,37,38].…”

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confidence: 99%

A Sparse Bayesian Imaging Technique for Efficient Recovery of Reservoir Channels With Time-Lapse Seismic Measurements

Sana

Ravanelli

Al-Naffouri

et al. 2016

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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

Cited by 21 publications

References 51 publications

Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

A Novel 3D Viscoelastic Acoustic Wave Equation Based Update Method for Reservoir History Matching

A Sparse Bayesian Imaging Technique for Efficient Recovery of Reservoir Channels With Time-Lapse Seismic Measurements

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