Download or read book Analyzing Reservoir and Overburden Impacts on Seismic and Electromagnetic Responses and the Applicability of Seismic and EM Methods in Deep Water Reservoir Characterization Through Forward and Inverse Modeling written by Anthony Kellogg and published by . This book was released on 2010 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seismic techniques have been widely used for hydrocarbon exploration. Recently, electromagnetic (EM) methods have drawn great attention in the area of reservoir characterization. However, few efforts have been made to explore the reservoir overburden impacts that affect the reliability of seismic, EM or joint methods for exploration. It is essential for successful reservoir hydrocarbon estimation to identify favorable overburden and reservoir conditions where reservoir fluid saturation can be reliably inferred from seismic data, EM data, or integrated geophysical information. This study evaluates the sensitivity of seismic and electromagnetic (EM) responses to hydrocarbon reservoir and overburden attributes through forward and inverse modeling.^First I generated baseline truth models from well log data, then varied the overburden and reservoir parameters (e.g., target layer thickness, porosity, saturations, etc.) within their physical ranges, producing multiple realistic subsurface models. Next, geophysical (seismic and EM) responses were computed for each model using seismic/EM forward modeling algorithms, and the differences in seismic and EM data between these realistic and baseline models were analyzed. Forward modeling results suggest that EM calculations are sensitive to several factors both in the reservoir and the overburden. Outside the reservoir, EM responses are most sensitive to seawater electrical conductivity, seawater depth and overburden sediment thickness. While among the parameters/properties in the reservoir, EM responses are most sensitive to gas saturations. Seismic data show strong responses to reservoir parameters, most notably to reservoir porosity.^After identifying the significant parameters, regression analyses using generalized linear models were performed and analyzed. Subsequent to exploring the sensitivity of seismic and EM responses to changes in overburden and reservoir parameters/attributes, the applicability of using these datasets for inverse modeling (parameter estimation) was evaluated using a Minimum Relative Entropy-based Bayesian stochastic inversion. Results suggest that estimations of reservoir parameters using high dimensional models can be rather difficult to do with great confidence. It was found that the more prior information available on the overburden unknowns, the closer the posterior estimation of the reservoir parameters will be to the actual values. Results also show that seismic methods are effective in estimating reservoir porosity, while EM has the potential for estimating reservoir saturations.^The integration of both, assuming enough information about the priors are known, has the potential to accurately estimate reservoir parameters presuming enough models are run. Informative prior knowledge about the field site, efficient sampling techniques, reduction of the parameter space, and computing capability are all necessary components for successful geophysical characterization of a petroleum reservoir, given the high dimensionality and non-uniqueness of the inverse problem.

Download or read book Seismic Reservoir Modeling written by Dario Grana and published by John Wiley & Sons. This book was released on 2021-05-04 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seismic reservoir characterization aims to build 3-dimensional models of rock and fluid properties, including elastic and petrophysical variables, to describe and monitor the state of the subsurface for hydrocarbon exploration and production and for CO2 sequestration. Rock physics modeling and seismic wave propagation theory provide a set of physical equations to predict the seismic response of subsurface rocks based on their elastic and petrophysical properties. However, the rock and fluid properties are generally unknown and surface geophysical measurements are often the only available data to constrain reservoir models far away from well control. Therefore, reservoir properties are generally estimated from geophysical data as a solution of an inverse problem, by combining rock physics and seismic models with inverse theory and geostatistical methods, in the context of the geological modeling of the subsurface. A probabilistic approach to the inverse problem provides the probability distribution of rock and fluid properties given the measured geophysical data and allows quantifying the uncertainty of the predicted results. The reservoir characterization problem includes both discrete properties, such as facies or rock types, and continuous properties, such as porosity, mineral volumes, fluid saturations, seismic velocities and density. Seismic Reservoir Modeling: Theory, Examples and Algorithms presents the main concepts and methods of seismic reservoir characterization. The book presents an overview of rock physics models that link the petrophysical properties to the elastic properties in porous rocks and a review of the most common geostatistical methods to interpolate and simulate multiple realizations of subsurface properties conditioned on a limited number of direct and indirect measurements based on spatial correlation models. The core of the book focuses on Bayesian inverse methods for the prediction of elastic petrophysical properties from seismic data using analytical and numerical statistical methods. The authors present basic and advanced methodologies of the current state of the art in seismic reservoir characterization and illustrate them through expository examples as well as real data applications to hydrocarbon reservoirs and CO2 sequestration studies.

Download or read book Uncertainty Analysis and Reservoir Modeling written by Y. Zee Ma and published by AAPG. This book was released on 2011-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Methods and Applications in Reservoir Geophysics written by David H. Johnston and published by SEG Books. This book was released on 2010 with total page 669 pages. Available in PDF, EPUB and Kindle. Book excerpt: The reservoir-engineering tutorial discusses issues and data critically important engineers. The geophysics tutorial has explanations of the tools and data in case studies. Then each chapter focuses on a phase of field life: exploration appraisal, development planning, and production optimization. The last chapter explores emerging technologies.

Download or read book Seismic Evaluation of Hydrocarbon Saturation in Deep Water Reservoirs written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: During this last period of the ''Seismic Evaluation of Hydrocarbon Saturation in Deep-Water Reservoirs'' project (Grant/Cooperative Agreement DE-FC26-02NT15342), we finalized integration of rock physics, well log analysis, seismic processing, and forward modeling techniques. Most of the last quarter was spent combining the results from the principal investigators and come to some final conclusions about the project. Also much of the effort was directed towards technology transfer through the Direct Hydrocarbon Indicators mini-symposium at UH and through publications. As a result we have: (1) Tested a new method to directly invert reservoir properties, water saturation, Sw, and porosity from seismic AVO attributes; (2) Constrained the seismic response based on fluid and rock property correlations; (3) Reprocessed seismic data from Ursa field; (4) Compared thin layer property distributions and averaging on AVO response; (5) Related pressures and sorting effects on porosity and their influence on DHI's; (6) Examined and compared gas saturation effects for deep and shallow reservoirs; (7) Performed forward modeling using geobodies from deepwater outcrops; (8) Documented velocities for deepwater sediments; (9) Continued incorporating outcrop descriptive models in seismic forward models; (10) Held an open DHI symposium to present the final results of the project; (11) Relations between Sw, porosity, and AVO attributes; (12) Models of Complex, Layered Reservoirs; and (14) Technology transfer Several factors can contribute to limit our ability to extract accurate hydrocarbon saturations in deep water environments. Rock and fluid properties are one factor, since, for example, hydrocarbon properties will be considerably different with great depths (high pressure) when compared to shallow properties. Significant over pressure, on the other hand will make the rocks behave as if they were shallower. In addition to the physical properties, the scale and tuning will alter our hydrocarbon indicators. Gas saturated reservoirs change reflection amplitudes significantly. The goal for the final project period was to systematically combine and document these various effects for use in deep water exploration and transfer this knowledge as clearly and effectively as possible.

Download or read book Integrating Rock Physics and Seismic Inversion for Reservoir Characterization in the Gulf of Mexico written by Oyedoyin Opeoluwa Oyetunji and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Seismic amplitude study is a crucial aspect in reservoir characterization as it helps to analyze seismic responses before interpretation. In this study, an attempt was made to identifying the reservoirs present in the High Island field at well locations. Rock physics modeling and seismic inversion were applied in an integrated approach to study the seismic response of these reservoirs and also delineate other hydrocarbon-charged reservoirs in the field. New elastic logs were generated and subsequently used for the rock physics analyses. Rock-property models using well-log data from the study area were evaluated. These models were used in analyzing the sand and shale log response of the study area. Well-log inversion is also carried out by minimizing the difference between modeled and measured logs. The cross-plot analyses from wells successfully distinguished between fluids and lithology effect in the area, these were subsequently confirmed by AVO modeling. The result showed that lower values of Lambda-Rho, Vp/Vs ratio and impedance values correlated with areas containing hydrocarbons. Three-dimensional seismic interpretation was also carried out to provide structural and stratigraphic information of the study area; the horizons reflect structural features including faults which could serve as a trapping mechanism for hydrocarbons. The picked horizons were used to guide the interpolation of the initial model used during seismic inversion. The seismic inversion helped delineate hydrocarbon reservoirs and also aided the propagation of reservoir parameters to include areal extent of the reservoir and to see how this varies within the field.

Download or read book Petroleum Abstracts written by and published by . This book was released on 1993 with total page 1752 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Seismic Reservoir Characterization written by Philippe Doyen and published by . This book was released on 2007 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Seismic Modeling of Complex Stratified Reservoirs written by Hung-Liang Lai and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Turbidite reservoirs in deep-water depositional systems, such as the oil fields in the offshore Gulf of Mexico and North Sea, are becoming an important exploration target in the petroleum industry. Accurate seismic reservoir characterization, however, is complicated by the heterogeneous of the sand and shale distribution and also by the lack of resolution when imaging thin channel deposits. Amplitude variation with offset (AVO) is a very important technique that is widely applied to locate hydrocarbons. Inaccurate estimates of seismic reflection amplitudes may result in misleading interpretations because of these problems in application to turbidite reservoirs. Therefore, an efficient, accurate, and robust method of modeling seismic responses for such complex reservoirs is crucial and necessary to reduce exploration risk. A fast and accurate approach generating synthetic seismograms for such reservoir models combines wavefront construction ray tracing with composite reflection coefficients in a hybrid modeling algorithm. The wavefront construction approach is a modern, fast implementation of ray tracing that I have extended to model quasishear wave propagation in anisotropic media. Composite reflection coefficients, which are computed using propagator matrix methods, provide the exact seismic reflection amplitude for a stratified reservoir model. This is a distinct improvement over conventional AVO analysis based on a model with only two homogeneous half spaces. I combine the two methods to compute synthetic seismograms for test models of turbidite reservoirs in the Ursa field, Gulf of Mexico, validating the new results against exact calculations using the discrete wavenumber method. The new method, however, can also be used to generate synthetic seismograms for the laterally heterogeneous, complex stratified reservoir models. The results show important frequency dependence that may be useful for exploration. Because turbidite channel systems often display complex vertical and lateral heterogeneity that is difficult to measure directly, stochastic modeling is often used to predict the range of possible seismic responses. Though binary models containing mixtures of sands and shales have been proposed in previous work, log measurements show that these are not good representations of real seismic properties. Therefore, I develop a new approach for generating stochastic turbidite models (STM) from a combination of geological interpretation and well log measurements that are more realistic. Calculations of the composite reflection coefficient and synthetic seismograms predict direct hydrocarbon indicators associated with such turbidite sequences. The STMs provide important insights to predict the seismic responses for the complexity of turbidite reservoirs. Results of AVO responses predict the presence of gas saturation in the sand beds. For example, as the source frequency increases, the uncertainty in AVO responses for brine and gas sands predict the possibility of false interpretation in AVO analysis.

Download or read book Bayesian Inversion Methods for Seismic Reservoir Characterization and Time lapse Studies written by Dario Grana and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation addresses mathematical methodologies for seismic reservoir characterization and time-lapse studies. Generally the main goal of reservoir modeling is to provide 3-dimensional models of the main properties in the reservoir in order to perform fluid flow simulations. These properties generally include rock properties, such as porosity and lithology; fluid properties, such as water and hydrocarbon saturations; and dynamic properties, such as pressure and permeability. None of these properties can be directly measured in the subsurface, therefore reservoir properties must be estimated from other measurements. In petroleum geophysics we generally have two kinds of measured data: well log data and seismic data. Well log data contain high resolution information about elastic and petrophysical properties, but they can only sample few locations of the reservoir. On the other side, seismic data cover the whole reservoir but the resolution is lower than well log data. Electromagnetic data are sometimes acquired in addition to seismic data to improve the reservoir description but the resolution is still limited. In order to obtain suitable models of the reservoir, we have to combine these two sources of information, wells and seismic, and integrate physical relations (rock physics and seismic modeling) with mathematical methodologies (inverse theory and probability and statistics). In particular by using a Bayesian approach to seismic and rock physics inversion we aim to obtain reservoir models of rock and fluid properties and the associated uncertainty. Since the resolution and the quality of seismic data are generally not ideal, uncertainty quantification plays a key role in reservoir modeling. This thesis includes three innovative methodologies for seismic reservoir characterization: the first method is a Bayesian inversion methodology suitable for reservoirs in exploration phases with a limited number of wells, the second method is a Bayesian sampling methodology that can provide multiple reservoir models honoring the given seismic dataset, the third one is a stochastic inversion methodology that provides high-detailed models suitable for reservoirs with a large number of wells. The key innovation in all these methods is the use of new statistical tools to describe the multimodal behavior of rock and properties in the reservoir and the direct integration of the rock physics model. The main principle of these methodologies is then extended to time-lapse studies to invert time-lapse seismic data and improve the reservoir description in terms of changes in rock and dynamic properties. The novelty of this method is the simultaneous inversion of the pre-production base seismic survey and repeated monitor surveys. This dissertation contributes to both deterministic and statistical seismic-based reservoir characterization. Complementary, I investigated velocity-pressure transforms to determine analytical physical models to describe the pressure effect on elastic properties and integrate these models in time-lapse reservoir studies. Finally I also developed a statistical methodology to integrate rock physics models in formation evaluation analysis and log-facies classification. All the proposed probabilistic reservoir-characterization techniques can predict reservoir models with multiple properties (static and dynamic) and the associated uncertainty. Multiple models can then be derived to run multiple scenarios and the corresponding risk analysis. All the methodologies were tested using synthetic data and applied to real case datasets. In the future, these methodologies could be integrated with history matching techniques to develop statistical methodologies for seismic history matching and improve reservoir description and monitoring by simultaneously matching seismic data and production data.

Download or read book Quantitative Reservoir Characterization Integrating Seismic Data and Geological Scenario Uncertainty written by Cheolkyun Jeong and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this dissertation is to characterize reservoir models quantitatively using seismic data and geological information. Its key contribution is to develop a practical workflow to integrate seismic data and geological scenario uncertainty. First, to address the uncertainty of multiple geological scenarios, we estimate the likelihood of all available scenarios using given seismic data. Starting with the probability given by geologists, we can identify more likely scenarios and less likely ones by comparing the pattern similarity of seismic data. Then, we use these probabilities to sample the posterior PDF constrained in multiple geological scenarios. Identifying each geological scenario in metric space and estimating the probability of each scenario given particular data helps to quantify the geological scenario uncertainty. Secondly, combining multiple-points geostatistics and seismic data in Bayesian inversion, we have studied some geological scenarios and forward simulations for seismic data. Due to various practical issues such as the complexity of seismic data and the computational inefficiency, this is not yet well established, especially for actual 3-D field datasets. To go from generating thousands of prior models to sampling the posterior, a faster and more computationally efficient algorithm is necessary. Thus, this dissertation proposes a fast approximation algorithm for sampling the posterior distribution of the Earth models, while maintaining a range of uncertainty and practical applicability. Lastly, the proposed workflow has been applied in an actual reservoir. The field, still in the early stage, has limited well data, seismic data, and some geological observations. Accordingly, the proposed workflow can guide several processes, from selecting geological scenarios to suggesting a set of models for decision makers. The case study, applied in a turbidite reservoir in West Africa, demonstrates the quantitative seismic reservoir characterization constrained to geological scenarios. It contains a well log study, rock physics modeling, a forward simulation for generating seismic responses, and object-based prior modeling. As the result, we could pick some promising geological scenarios and its geological parameters from seismic data using distance-based pattern similarity. Next, based on the selected geological scenarios, Metropolis sampler using Adaptive Spatial Resampling (M-ASR) successfully sampled the posterior conditioned to all available data and geological scenario uncertainty.

Download or read book Seismic Data Integration and Multi objective Optimization for 3D Reservoir Characterization and Model Building written by Mohammad Emami Niri and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: [Truncated] Reservoir modeling is the practice of generating numerical representations of reservoir conditions and properties on the basis of geological, geophysical and engineering data measured on the Earth's surface or in depth at a limited number of borehole locations. Building an accurate reservoir model is a fundamental step of reservoir characterization and fluid flow performance forecasting, and has direct impact on reservoir management strategies, risk/uncertainty analyses and key business decisions. Seismic data, due to its high spatial resolution, plays a key role not only in defining the reservoir structure and geometry, but also in constraining the reservoir property variations. However, integration of 3D and time-lapse 4D seismic data into reservoir modeling and history matching processes poses a significant challenge due to the frequent mismatch between the initial reservoir model, the reservoir geology, and the pre-production seismic data. The key objective of this thesis is to investigate, develop and apply innovative solutions and methods to incorporate seismic data in the reservoir characterization and model building processes, and ultimately improve the consistency of the reservoir models with both geological and geophysical measurements. In this thesis we first analyze the issues that have a significant impact on the (mis)match of the initial reservoir model with well logs and 3D seismic data. These issues include the incorporation of various seismic constraints in reservoir property modeling, the sensitivity of the results to realistic noise in seismic data, and to geostatistical modeling parameters, and the uncertainties associated with quantitative integration of seismic data in reservoir property modeling. Inherent uncertainties and noise in real data measurements may result in conflicting geological and geophysical information for a given area; a realistic subsurface model can then only be produced by combining the datasets in some optimal manner. One approach to solving this problem is by joint inversion of the various geological and/or geophysical datasets. In this thesis we develop a new multi-objective optimization method to estimate subsurface geomodels using a stochastic search technique that allows a variety of direct and indirect measurements to simultaneously constrain the model. The main advantage of our method is its ability to define multiple objective functions for a variety of data types and constraints, and simultaneously minimize the data misfits. Using our optimization approach, the resulting models converge towards Pareto fronts (a set of best compromise model solutions). This approach is applicable in many Earth science disciplines: hydrology and ground water analyses, geothermal studies, exploration and recovery of fossil fuel energy resources, and CO2 geosequestration, among others.

Download or read book A Practical Guide to Seismic Reservoir Characterization written by Timothy Tylor-Jones and published by Springer Nature. This book was released on 2023-01-11 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers in detail the entire workflow for quantitative seismic interpretation of subsurface modeling and characterization. It focusses on each step of the geo-modeling workflow starting from data preconditioning and wavelet extraction, which is the basis for the reservoir geophysics described and introduced in the following chapters. This book allows the reader to get a comprehensive insight of the most common and advanced workflows. It aims at graduate students related to energy (hydrocarbons), CO2 geological storage, and near surface characterization as well as professionals in these industries. The reader benefits from the strong and coherent theoretical background of the book, which is accompanied with real case examples.

Download or read book Reservoir Sedimentation written by G.W. Annandale and published by Elsevier. This book was released on 1987-01-01 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research on reservoir sedimentation in recent years has been aimed mainly at water resources projects in developing countries. These countries, especially in Africa, often have to cope with long droughts, flash floods and severe erosion problems. Large reservoir capacities are required to capture water provided by flash floods so as to ensure the supply of water in periods of drought. The problem arising however is that these floods, due to their tremendous stream power, carry enormous volumes of sediment which, due to the size of reservoirs, are virtually deposited in toto in the reservoir basin, leading to fast deterioration of a costly investment. Accurate forecasting of reservoir behaviour is therefore of the utmost importance.This book fills a gap in current literature by providing in one volume comprehensive coverage of techniques required to practically investigate the effects sediment deposition in reservoirs has on the viability of water resources projects. Current techniques for practically estimating sediment yield from catchments, estimating the volume of sediment expected to deposit in reservoirs, predicting sediment distribution and calculating scour downstream of reservoirs are evaluated and presented. The liberal use of diagrams and graphs to explain the various techniques enhances understanding and makes practical application simple. A major feature of the book is the application of stream power theory to explain the process of reservoir sedimentation and to develop four new methods for predicting sediment distribution in reservoirs.The book is primarily directed at practising engineers involved in the planning and design of water resources projects and at post-graduate students interested in this field of study.

Download or read book Reservoir Geophysics written by William L. Abriel and published by SEG Books. This book was released on 2008 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes the main business drivers of the operator and how seismic data help address subsurface uncertainties. This volume discusses delineation, development, production, and geophysics applications in heavy-oil and carbonate reservoirs, and includes problems based on actual projects. Illustrations contain examples that focus on business value.

Download or read book HEC 6 written by and published by . This book was released on 1995 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Seismic Driven Reservoir Characterization for Porosity Estimation written by Muhammad Naeem and published by . This book was released on 2015-04-11 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: