Integrated reservoir characterization: Beyond tomography

Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 354-364 ◽  
Author(s):  
Larry Lines ◽  
Henry Tan ◽  
Sven Treitel ◽  
John Beck ◽  
Richard Chambers ◽  
...  
Keyword(s):  
History Matching ◽  
Preferential Flow ◽  
Reservoir Characterization ◽  
Seismic Anisotropy ◽  
Flow Direction ◽  
Geophysical Methods ◽  
Reservoir Properties ◽  
Traveltime Tomography ◽  
Sonic Log ◽  
Primary Water

In 1992, there was a collaborative effort in reservoir geophysics involving Amoco, Conoco, Schlumberger, and Stanford University in an attempt to delineate variations in reservoir properties of the Grayburg unit in a West Texas [Formula: see text] pilot at North Cowden Field. Our objective was to go beyond traveltime tomography in characterizing reservoir heterogeneity and flow anisotropy. This effort involved a comprehensive set of measurements to do traveltime tomography, to image reflectors, to analyze channel waves for reservoir continuity, to study shear‐wave splitting for borehole stress‐pattern estimation, and to do seismic anisotropy analysis. All these studies were combined with 3-D surface seismic data and with sonic log interpretation. The results are to be validated in the future with cores and engineering data by history matching of primary, water, and [Formula: see text] injection performance. The implementation of these procedures should provide critical information on reservoir heterogeneities and preferential flow direction. Geophysical methods generally indicated a continuous reservoir zone between wells.

scholarly journals SEISMIC TRAVELTIME TOMOGRAPHY IN THE DOM JOÃO FIELD, RECÔNCAVO BASIN, BRAZIL

2015 ◽  
Vol 33 (1) ◽  
pp. 89
Author(s):  
Naiane Pereira de Oliveira ◽  
Amin Bassrei
Keyword(s):  
Reservoir Characterization ◽  
New Technologies ◽  
Real Data ◽  
Seismic Inversion ◽  
P Wave ◽  
Gradient Algorithm ◽  
High Rate ◽  
Traveltime Tomography ◽  
Sonic Log ◽  
High Resolution Images

ABSTRACT. Tomography was incorporated in Exploration Geophysics with the intention of providing high-resolution images of regions in Earth’s subsurface that are characterized as potential reservoirs. In this work, seismic traveltime tomography in the transmission mode was applied to real data from the Dom João Field, Recôncavo Basin, State of Bahia, Brazil. This basin represents a landmark of oil exploration in Brazil and has been intensively studied since the 1950’s. Today, the Recôncavo Basin is still the principal oil producer in the State of Bahia, but there is a demand for new technologies, especially for mature fields, to improve hydrocarbon recovery. Acoustic ray tracing for the computation of traveltimes was used for forward modeling, and the conjugate gradient algorithm with regularization through derivative matrices was used as the inverse procedure. The estimated tomograms were consistent with available data from a sonic log near the acquisition area in terms of the layer geometry, as well as the P-wave velocity range. The results showed that traveltime tomography is feasible for the characterization of reservoirs with a high rate of vertical change, similar to the Dom Jo˜ao Field.Keywords: traveltime tomography, seismic inversion, regularization, reservoir characterization, Recˆoncavo Basin.RESUMO. A tomografia foi incorporada na Geofísica de Exploração justamente para fornecer imagens de alta resolução de regiões do interior da Terra, consideradas como potenciais reservatórios. Neste trabalho aplicamos a tomografia sísmica de tempos de trânsito no modo de transmissão em dados reais do Campo de Dom João, Bacia do Recôncavo, Estado da Bahia, Brasil. Esta bacia representa um marco da exploração de petróleo no Brasil e vem sendo exaustivamente estudada desde a década de 1950. Embora haja uma demanda por novas tecnologias, em especial para campos maduros, com o propósito de se aumentar a recuperação de hidrocarbonetos, a Bacia do Recôncavo é ainda a principal produtora do Estado da Bahia. Para o procedimento da modelagem direta foi utilizado o traçado de raios acústicos e para o procedimento inverso foi utilizado o algoritmo do gradiente conjugado com regularização através de matrizes de derivadas. Os tomogramas estimados foram consistentes com os dados provenientes do perfil sõnico de um poço próximo ao levantamento tomográfico analisado, tanto em termos de geometria de camadas, como também na faixa de velocidades da onda P. Os resultados mostraram que a tomografia de tempos de trânsito é viável para a caracterização de reservatórios com elevada taxa de variação vertical, que é o caso do Campo de Dom João.Palavras-chave: tomografia de tempos de trânsito, inversão sísmica, regularização, caracterização de reservatórios, Bacia do Recôncavo.

Comparing Steam Flood Analytical and Simulation Models ~ Strengths and Limitations

2021 ◽  
Author(s):  
Thomas J. Hampton ◽  
Mohamed El-Mandouh ◽  
Stevan Weber ◽  
Tirth Thaker ◽  
K.. Patel ◽  
...  
Keyword(s):  
History Matching ◽  
Reservoir Characterization ◽  
Simulation Models ◽  
Analytical Models ◽  
Reservoir Properties ◽  
Advantages And Disadvantages ◽  
Single Pattern ◽  
Steam Flood ◽  
Methods Analytical ◽  
Or History

Abstract Mathematical Models are needed to aid in defining, analyzing, and quantifying solutions to design and manage steam floods. This paper discusses two main modeling methods – analytical and numerical simulation. Decisions as to which method to use and when to use them, requires an understanding of assumptions used, strengths, and limitations of each method. This paper presents advantages and disadvantages through comparison of analytical vs simulation when reservoir characterization becomes progressively more complex (dip, layering, heterogeneity between injector/producer, and reservoir thickness).While there are many analytical models, three analytical models are used for this paper:Marx & Langenheim, Modified Neuman, and Jeff Jones.The simulator used was CMG Stars on single pattern on both 5 Spot and 9 Spot patterns and Case 6 of 9 patterns, 5-Spot. Results were obtained using 6 different cases of varying reservoir properties based on Marx & Langenheim, Modified Neuman, and Jeff Jones models.Simulation was also done on each of the 6 cases, using Modified Neuman steam rates and then on Jeff Jones Steam rates using 9-Spot and 5-Spot patterns.This was done on predictive basis on inputs provided, without adjusting or history matching on analog or historical performance.Optimization runs using Particle Swarm Optimization was applied on one case in minimizing SOR and maximize NPV. Conclusion from comparing cases is that simulation is needed for complex geology, heterogeneity, and changes in layering. Also, simulation can be used for maximizing economics using AI based optimization tool. While understanding limitations, the analytical models are good for quick looks such as screening, scoping design, some surveillance, and for conceptual understanding of basic steam flood on uniform geologic properties. This paper is innovative in comparison of analytical models and simulation modeling.Results that quantify differences of oil rate, SOR, and injection rates (Neuman and Jeff Jones) impact on recovery factors is presented.

scholarly journals Porosity estimation in the Fort Worth Basin constrained by 3D seismic attributes integrated in a sequential Bayesian simulation framework

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. M67-M80 ◽  
Author(s):  
Martin Blouin ◽  
Mickaele Le Ravalec ◽  
Erwan Gloaguen ◽  
Mathilde Adelinet
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Geophysical Methods ◽  
Seismic Attributes ◽  
Seismic Inversion ◽  
Fort Worth ◽  
3D Seismic ◽  
Reservoir Properties ◽  
Fort Worth Basin ◽  
Porosity Estimation

The accurate inference of reservoir properties such as porosity and permeability is crucial in reservoir characterization for oil and gas exploration and production as well as for other geologic applications. In most cases, direct measurements of those properties are done in wells that provide high vertical resolution but limited lateral coverage. To fill this gap, geophysical methods can often offer data with dense 3D coverage that can serve as proxy for the variable of interest. All the information available can then be integrated using multivariate geostatistical methods to provide stochastic or deterministic estimate of the reservoir properties. Our objective is to generate multiple scenarios of porosity at different scales, considering four formations of the Fort Worth Basin altogether and then restricting the process to the Marble Falls limestones. Under the hypothesis that a statistical relation between 3D seismic attributes and porosity can be inferred from well logs, a Bayesian sequential simulation (BSS) framework proved to be an efficient approach to infer reservoir porosity from an acoustic impedance cube. However, previous BBS approaches only took two variables upscaled at the resolution of the seismic data, which is not suitable for thin-bed reservoirs. We have developed three modified BSS algorithms that better adapt the BSS approach for unconventional reservoir petrophysical properties estimation from deterministic prestack seismic inversion. A methodology that includes a stochastic downscaling procedure is built and one that integrates two secondary downscaled constraints to the porosity estimation process. Results suggest that when working at resolution higher than surface seismic, it is better to execute the workflow for each geologic formation separately.

Regeneration of Initial Ensembles With Facies Analysis for Efficient History Matching

2017 ◽  
Vol 139 (4) ◽  
Author(s):  
Byeongcheol Kang ◽  
Jonggeun Choe
Keyword(s):  
History Matching ◽  
Reservoir Characterization ◽  
Principal Component ◽  
The Other ◽  
Limited Information ◽  
Production Rates ◽  
Reservoir Properties ◽  
Principal Characteristics ◽  
Reservoir Models ◽  
Production History

Reservoir characterization is needed for estimating reservoir properties and forecasting production rates in a reliable manner. However, it is challenging to figure out reservoir properties of interest due to limited information. Therefore, well-designed reservoir models, which reflect characteristics of a true field, should be selected and fine-tuned. We propose a novel scheme of generating initial reservoir models by using static data and production history data available. We select representative reservoir models by projecting reservoir models onto a two-dimensional (2D) plane using principal component analysis (PCA) and calculating errors of production rates against observed data. These selected models, which will have similar geological properties with the reference, are used to regenerate models by perturbing along the boundary of the different facies. These regenerated models have all the different facies distributions but share principal characteristics based on the selected models. We compare cases using 400 ensemble members, 100 models with unbiased uniform sampling, and 100 regenerated models by the proposed method. We analyze two synthetic reservoirs with different permeability distributions: one is a typical heterogeneous reservoir and the other is a channel reservoir with a bimodal permeability distribution. Compared to the cases using all the 400 models with ensemble Kalman filter (EnKF), the simulation time is dramatically reduced to 4.7%, while the prediction quality on oil and water productions is improved. Even in the more complex reservoir case, the proposed method shows great improvements with reduced uncertainties against the other cases.

The effect of seismic anisotropy on reservoir characterization

2005 ◽  
Author(s):  
Said Amiri Besheli ◽  
Milovan Urosevic ◽  
Ruiping Li
Keyword(s):  
Reservoir Characterization ◽  
Seismic Anisotropy

Latest developments in seismic texture analysis for subsurface structure, facies, and reservoir characterization: A review

Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. W1-W13 ◽  
Author(s):  
Dengliang Gao
Keyword(s):  
Texture Analysis ◽  
Reservoir Characterization ◽  
Preliminary Test ◽  
Seismic Facies ◽  
Least Squares Regression ◽  
Reservoir Properties ◽  
Seismic Amplitude ◽  
Texture Model ◽  
Facies Classification ◽  
Analysis Window

In exploration geology and geophysics, seismic texture is still a developing concept that has not been sufficiently known, although quite a number of different algorithms have been published in the literature. This paper provides a review of the seismic texture concepts and methodologies, focusing on latest developments in seismic amplitude texture analysis, with particular reference to the gray level co-occurrence matrix (GLCM) and the texture model regression (TMR) methods. The GLCM method evaluates spatial arrangements of amplitude samples within an analysis window using a matrix (a two-dimensional histogram) of amplitude co-occurrence. The matrix is then transformed into a suite of texture attributes, such as homogeneity, contrast, and randomness, which provide the basis for seismic facies classification. The TMR method uses a texture model as reference to discriminate among seismic features based on a linear, least-squares regression analysis between the model and the data within an analysis window. By implementing customized texture model schemes, the TMR algorithm has the flexibility to characterize subsurface geology for different purposes. A texture model with a constant phase is effective at enhancing the visibility of seismic structural fabrics, a texture model with a variable phase is helpful for visualizing seismic facies, and a texture model with variable amplitude, frequency, and size is instrumental in calibrating seismic to reservoir properties. Preliminary test case studies in the very recent past have indicated that the latest developments in seismic texture analysis have added to the existing amplitude interpretation theories and methodologies. These and future developments in seismic texture theory and methodologies will hopefully lead to a better understanding of the geologic implications of the seismic texture concept and to an improved geologic interpretation of reflection seismic amplitude.

A Fast Gridding Method for Capturing Geological Complexity and Uncertainty

2021 ◽  
Author(s):  
Yifei Xu ◽  
Priyesh Srivastava ◽  
Xiao Ma ◽  
Karan Kaul ◽  
Hao Huang
Keyword(s):  
Efficient Method ◽  
Reservoir Simulation ◽  
History Matching ◽  
Mapping Method ◽  
Reservoir Properties ◽  
Structural Framework ◽  
Assisted History Matching ◽  
Grid Topology ◽  
Geological Complexity ◽  
Complex Channel

Abstract In this paper, we introduce an efficient method to generate reservoir simulation grids and modify the fault juxtaposition on the generated grids. Both processes are based on a mapping method to displace vertices of a grid to desired locations without changing the grid topology. In the gridding process, a grid that can capture stratigraphical complexity is first generated in an unfaulted space. The vertices of the grid are then displaced back to the original faulted space to become a reservoir simulation grid. The resulting reversely mapped grid has a mapping structure that allows fast and easy fault juxtaposition modification. This feature avoids the process of updating the structural framework and regenerating the reservoir properties, which may be time-consuming. To facilitate juxtaposition updates within an assisted history matching workflow, several parameterized fault throw adjustment methods are introduced. Grid examples are given for reservoirs with Y-faults, overturned bed, and complex channel-lobe systems.

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