Download or read book Geologic Modeling and Data Assimilation for CO2 Sequestration in Point Bar Reservoirs written by Ismael Dawuda and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The target reservoirs in many CO2 sequestration projects exhibit point bar geology characterized by the presence of shale drapes that can act as barriers to prevent the leakage of CO2. However, these shale drapes can also act as flow barriers and impede the displacement of CO2 in such reservoirs and restrict the storage volume. Therefore, developing a framework for modeling point bars and their associated heterogeneities is important. Yet, for the point bar model to be geologically realistic and reliable for predicting the displacement of the CO2 plume during sequestration, it should be calibrated by assimilating historical production/injection data to reduce the uncertainties associated with predictions of flow performance. Even so, due to the complex geologic heterogeneity exhibited by point bars, there is likely to be significant residual uncertainty even after assimilating historical flow performance related data. The calibrated models are further refined by assimilating timelapse seismic data in a Bayesian model selection workflow to sub-select the most-probable models that best reflect the reservoir characteristics closely. Given the interlinked nature of these modeling efforts, this dissertation proposes an integrated modeling workflow to accomplish the research objectives. The workflow begins with detailed geometric and geologic modeling of point bar reservoirs, and subsequent calibration of the models by assimilating CO2 injection data and time-lapse seismic information. A stochastic approach that considers the processes leading to the deposition of the point bar is proposed to model the point bar and its associated heterogeneities. The method uses geometric functions to model the areal and vertical dimensions of the point bar reservoir. Preserving the curvilinear continuity of the point bar geometry is very difficult and this has been accomplished by implementing a gridding scheme that accounts for the aerial geometry of the accretion surfaces as well as the sigmoidal geometry of the inclined heterolithic stratifications. Also, the spatial continuity of the unique heterogeneities that characterize point bar reservoirs was honored by incorporating a grid transformation scheme in the geostatistical simulation of the reservoir properties. The residual uncertainty associated with the geological modeling process was represented by generating several realizations of point bar reservoir models. The model calibration workflow seeks to reduce the uncertainty associated with the prediction of reservoir properties over the ensemble of point bar reservoir models. The workflow developed in this research addresses two challenges common to many history matching techniques: (1) failure to account for uncertainties in reservoir geometry despite the influence that the reservoir architecture can have on reservoir response variables, (2) inability to handle the non-Gaussian relationship between the primary state variables and secondary variables for reservoirs with complex heterogeneities (such as point bars) within current ensemble-based schemes. These challenges were addressed in a hierarchical, two-step approach using ensemble-based data assimilation techniques. In step 1, we tackled the first challenge by implementing ensemble Kalman Filter (EnKF) to update the geometry of the point bar reservoir. For step 2, we used the updated reservoir geometry determined in step 1 to tackle the second problem by implementing a modified Indicator-based Data Assimilation (InDA) to update the permeability distribution in the point bar system. To accommodate the curvilinear geometry of the reservoir implemented while still implementing InDA in a Cartesian framework, we incorporated a grid transformation scheme. This two-step model calibration approach reduces but does not eliminate the uncertainty associated with the models for the point bar reservoir. Further reduction in uncertainty is possible by integrating additional data in the form of time-lapse information. In this research, we implement a Bayesian model selection workflow to further reduce the uncertainty associated with the models for the point bar reservoir. The model selection algorithm is used to create a posterior set of models that reflect the time-lapse seismic information that may be available for the field site. The algorithm proceeds by: (1) computing discrete Fréchet distances to quantify the similarity in post-injection seismic responses obtained from a large prior ensemble of models, (2) combining multidimensional scaling with k-means clustering, to partition the models into subgroups based on their seismic responses, (3) performing Bayesian computations in the reduced model space to select the subgroup of models that yield response closest to the observed seismic information, and (4) iteratively sampling the posterior models, to further refine the selection of the model clusters. The applicability of the entire integrated workflow to a real field scenario is demonstrated, using the CO2 injection and timelapse seismic dataset for the Cranfield reservoir in Mississippi. The final ensemble of selected models can be used to assess the uncertainty in predicting CO2 storage capacity and the future displacement of CO2 plume.

Download or read book Data Assimilation Tools for CO2 Reservoir Model Development A Review of Key Data Types Analyses and Selected Software written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Pacific Northwest National Laboratory (PNNL) has embarked on an initiative to develop world-class capabilities for performing experimental and computational analyses associated with geologic sequestration of carbon dioxide. The ultimate goal of this initiative is to provide science-based solutions for helping to mitigate the adverse effects of greenhouse gas emissions. This Laboratory-Directed Research and Development (LDRD) initiative currently has two primary focus areas--advanced experimental methods and computational analysis. The experimental methods focus area involves the development of new experimental capabilities, supported in part by the U.S. Department of Energy's (DOE) Environmental Molecular Science Laboratory (EMSL) housed at PNNL, for quantifying mineral reaction kinetics with CO2 under high temperature and pressure (supercritical) conditions. The computational analysis focus area involves numerical simulation of coupled, multi-scale processes associated with CO2 sequestration in geologic media, and the development of software to facilitate building and parameterizing conceptual and numerical models of subsurface reservoirs that represent geologic repositories for injected CO2. This report describes work in support of the computational analysis focus area. The computational analysis focus area currently consists of several collaborative research projects. These are all geared towards the development and application of conceptual and numerical models for geologic sequestration of CO2. The software being developed for this focus area is referred to as the Geologic Sequestration Software Suite or GS3. A wiki-based software framework is being developed to support GS3. This report summarizes work performed in FY09 on one of the LDRD projects in the computational analysis focus area. The title of this project is Data Assimilation Tools for CO2 Reservoir Model Development. Some key objectives of this project in FY09 were to assess the current state-of-the-art in reservoir model development, the data types and analyses that need to be performed in order to develop and parameterize credible and robust reservoir simulation models, and to review existing software that is applicable to these analyses. This report describes this effort and highlights areas in which additional software development, wiki application extensions, or related GS3 infrastructure development may be warranted.

Download or read book Geologic Carbon Sequestration written by V. Vishal and published by Springer. This book was released on 2016-05-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This exclusive compilation written by eminent experts from more than ten countries, outlines the processes and methods for geologic sequestration in different sinks. It discusses and highlights the details of individual storage types, including recent advances in the science and technology of carbon storage. The topic is of immense interest to geoscientists, reservoir engineers, environmentalists and researchers from the scientific and industrial communities working on the methodologies for carbon dioxide storage. Increasing concentrations of anthropogenic carbon dioxide in the atmosphere are often held responsible for the rising temperature of the globe. Geologic sequestration prevents atmospheric release of the waste greenhouse gases by storing them underground for geologically significant periods of time. The book addresses the need for an understanding of carbon reservoir characteristics and behavior. Other book volumes on carbon capture, utilization and storage (CCUS) attempt to cover the entire process of CCUS, but the topic of geologic sequestration is not discussed in detail. This book focuses on the recent trends and up-to-date information on different storage rock types, ranging from deep saline aquifers to coal to basaltic formations.

Download or read book Data Driven Analytics for the Geological Storage of CO2 written by Shahab Mohaghegh and published by CRC Press. This book was released on 2018-05-20 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.

Download or read book Optimization and Monitoring of Geological Carbon Storage Operations written by David A. Cameron and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon capture and storage is a climate change mitigation technology that involves collecting and injecting CO2 emissions from fossil fuel burning power plants, or other point source emitters, into deep underground geologic formations such as brine aquifers. In carbon storage operations, structurally trapped CO2 that is mobile (i.e., able to flow as a free-CO2 phase) will be susceptible to leakage if the cap rock is compromised. Thus, the environmental and economic risks associated with a sequestration project can be reduced by facilitating other storage mechanisms and minimizing the amount of structurally trapped CO2. Data assimilation is also essential if we are to reduce the uncertainty in the CO2 plume location and to quickly identify any leakage through the cap rock. In this work we develop and apply computational optimization procedures to minimize the risk of CO2 leakage and to perform data assimilation in order to identify the location of the CO2 plume and detect CO2 leakage through the cap rock. The risk of leakage is quantified both in terms of the mobile CO2 in the formation and in terms of the total mobility of free CO2 at the top of the storage aquifer. Risk minimization is accomplished by determining optimum locations and time-varying injection rates for a set of horizontal CO2 injection wells. Both Hooke-Jeeves Direct Search and Particle Swarm Optimization algorithms are used for this purpose. A brine cycling procedure, in which brine is periodically produced at the bottom of the aquifer and reinjected at the top of the aquifer, is also considered, and the parameters associated with this operation are optimized. For data assimilation (or history matching), aquifer geology is represented in terms of a relatively small number of parameters using a Karhunen-Loeve (K-L) expansion. Sensor and CO2 injection-well data provide the measurements to be matched. A procedure for optimizing the placement of monitoring wells and the weights of the various types of measured data, with the goal of maximizing the efficacy of the history matching procedure, is also presented. Optimization results for both deterministic and uncertain aquifer models (in the latter case, the aquifer is represented using multiple realizations) are presented for a variety of cases, and reduction in the risk of leakage is consistently achieved. Specifically, by optimizing well placement and control (with known geology), the mobile CO2 fraction is reduced from around 0.32 to 0.22, and the total mobility is decreased by around 39%. For cases with uncertain geology, the reduction in mobile CO2 from optimization is only 7%, highlighting the need for a-priori geologic characterization. Optimizing brine cycling processes leads to further risk reduction, and a plot of risk of leakage versus pore volume of brine injected (which is related to cost) provides a Pareto front for a bi-objective optimization involving these two variables as objectives. The data assimilation procedure is shown to improve predictions for the CO2 plume location relative to results from prior geological models. Specifically, in a series of tests, this procedure reduces the average error in the predicted CO2 mobility in the top layer of the model (which is the quantity of interest) by 46% relative to the error using the prior model. Finally, we investigate the early detection of leaks in the cap rock using pressure data. We introduce a three-region model to quantify the amount of leakage for a large number of leakage cases (some including multiple leaks). A data assimilation method is applied to determine leakage locations and permeabilities for a number of cases, with pressures at sensor wells and injection wells providing the measured data. Particle Swarm Optimization is used for the minimizations associated with this data assimilation problem. A data-rich scenario with nine sensor wells (completed in the overlying aquifer and storage formation) and a data-scarce scenario with four sensor wells (completed only in the overlying aquifer) are considered. Results indicate that the history matching procedure effectively locates leakage positions in cases with a single leak, for both the data-rich and data-scarce scenarios. For cases with multiple leaks, however, the procedure is less reliable, though the data-rich scenario is shown to provide better matches than the data-scarce scenario.

Download or read book Mechanisms for CO2 Sequestration in Geological Formations and Enhanced Gas Recovery written by Roozbeh Khosrokhavar and published by Springer. This book was released on 2015-10-28 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives background information why shale formations in the world are important both for storage capacity and enhanced gas recovery (EGR). Part of this book investigates the sequestration capacity in geological formations and the mechanisms for the enhanced storage rate of CO2 in an underlying saline aquifer. The growing concern about global warming has increased interest in geological storage of carbon dioxide (CO2). The main mechanism of the enhancement, viz., the occurrence of gravity fingers, which are the vehicles of enhanced transport in saline aquifers, can be visualized using the Schlieren technique. In addition high pressure experiments confirmed that the storage rate is indeed enhanced in porous media. The book is appropriate for graduate students, researchers and advanced professionals in petroleum and chemical engineering. It provides the interested reader with in-depth insights into the possibilities and challenges of CO2 storage and the EGR prospect.

Download or read book Geological Sequestration of Carbon Dioxide written by Luigi Marini and published by Elsevier. This book was released on 2006-10-12 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contents of this monograph are two-scope. First, it intends to provide a synthetic but complete account of the thermodynamic and kinetic foundations on which the reaction path modeling of geological CO2 sequestration is based. In particular, a great effort is devoted to review the thermodynamic properties of CO2 and of the CO2-H2O system and the interactions in the aqueous solution, the thermodynamic stability of solid product phases (by means of several stability plots and activity plots), the volumes of carbonation reactions, and especially the kinetics of dissolution/precipitation reactions of silicates, oxides, hydroxides, and carbonates. Second, it intends to show the reader how reaction path modeling of geological CO2 sequestration is carried out. To this purpose the well-known high-quality EQ3/6 software package is used. Setting up of computer simulations and obtained results are described in detail and used EQ3/6 input files are given to guide the reader step-by-step from the beginning to the end of these exercises. Finally, some examples of reaction-path- and reaction-transport-modeling taken from the available literature are presented. The results of these simulations are of fundamental importance to evaluate the amounts of potentially sequestered CO2, and their evolution with time, as well as the time changes of all the other relevant geochemical parameters (e.g., amounts of solid reactants and products, composition of the aqueous phase, pH, redox potential, effects on aquifer porosity). In other words, in this way we are able to predict what occurs when CO2 is injected into a deep aquifer. * Provides applications for investigating and predicting geological carbon dioxide sequestration * Reviews the geochemical literature in the field * Discusses the importance of geochemists in the multidisciplinary study of geological carbon dioxide sequestration

Download or read book An Uncertainty Analysis of Modeling Geologic Carbon Sequestration in a Naturally Fractured Reservoir at Teapot Dome Wyoming written by Ye Li and published by . This book was released on 2014 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study presents an uncertainty analysis of Geologic Carbon Sequestration modeling in a naturally fractured reservoir at Teapot Dome, Wyoming. Structural & stratigraphic, residual, and solubility trapping mechanisms are the focus of this study, while mineral trapping is not considered. A reservoir-scale geologic model is built to model CO2 storage in the Tensleep Sandstone using a variety of site characterization data that have been collected, screened for accuracy, and analyzed. These data are from diverse sources, such as reservoir geology, geophysics, petrophysics, engineering, and analogs. Because fluid flow occurs in both matrix and fractures of the Tensleep Sandstone, both systems of heterogeneity must be incorporated into the geologic model. The matrix heterogeneity of the geologic model is developed through a hierarchical process of structural modeling, facies modeling, and petrophysical modeling. In structural modeling, the framework of the reservoir is conditioned to seismic data and well log interpretations. Based on the concept of flow units, the facies model, which is conditioned to a global vertical facies proportion curve that acts as `soft' data, is built geostatistically by the Sequential Indicator Simulation method. Then, the petrophysical properties (porosity) are modeled geostatistically within each facies through the Sequential Gaussian Simulation approach. A Discrete Fracture Network (DFN) is adopted as the method to model the distribution of open natural fractures in the reservoir. Basic inputs for the DFN model are derived from FMI logs, cores, and analogs. In addition, in combination with an artificial neural network analysis, 3D seismic attributes are used as fracture drivers to guide the modeling of fracture intensity distribution away from the boreholes. In DFN models, power laws are adopted to define the distribution of fracture intensity, length and aperture. To understand the effect of model complexity on CO2 storage predictions, a suite of increasingly simplified conceptual geologic model families are created with decreasing amount of site characterization data: a hierarchical stochastic model family conditioned to ' soft' data (FAM4), a simple stochastic facies model family (FAM3), a simple stochastic porosity model family (FAM2), and a homogeneous model family (FAM1). These families, representing alternative conceptual geologic models built with increasing reduced data, are simulated with the same CO2 injection test (20 years of injection at 1,000 Mscf/day), followed by 80 years of monitoring. Using the Design of Experiment, an efficient sensitivity analysis (SA) is conducted for all families, systematically varying uncertain input parameters, while assuming identical well configurations, injection rates, bottom-hole pressure constraints, and boundary conditions. The SA results are compared among the families to identify parameters that have the first order impact on predicting the CO2 storage ratio (SR) at two different time scales, i.e., end of injection and end of monitoring. This comparison indicates that, for this naturally fractured reservoir, the facies model is necessary to study the sensitivity characteristics of predicting the CO 2 storage behavior. The SA results identify matrix relative permeability, fracture aperture of fracture set 1, and fracture aperture of fracture set 2 as the statistically important factors. Based on the results of the SA, a response surface analysis is conducted to generate prediction envelopes of the CO2 storage ratio, which are also compared among the families at both times. Its results demonstrate that the SR variation due to the different modeling choices is relatively small. At the proposed storage site, as more than 90% of injected CO2 is probably mobile, short-term leakage risk is considered large, and it depends on the sealing ability of top formations.

Download or read book CO2 Storage in Deltaic Environments of Deposition written by Emily Christine Beckham and published by . This book was released on 2018 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon sequestration in geologic reservoirs is a proven method for reducing greenhouse gas emissions. Deltaic deposits are attractive candidates for CO2 storage projects due to their prominent role as hydrocarbon reservoirs. This research informs subsurface deltaic reservoir characterization and performance for carbon sequestration through integration of geocellular modeling, outcrop analyses, and seismic mapping of prospective offshore CO2 reservoirs. Results emphasize the importance of recognizing sequence stratigraphic architectures for predicting CO2 migration. Initially, a model of a deltaic system was generated from a prior laboratory flume deposit to better understand fundamental (but generalized) aspects of reservoir and seal performance. This model was scaled and assigned geologic properties, generating a novel and extremely high-resolution geologic model. Physical architectures represented in the geologic model are consistent with global examples of deltaic reservoirs as well as the facies, stratal stacking pattern, and grain size variability in outcrops studied in this research. Twenty CO2 injection simulations were run on the geologic model to understand the relationship between reservoir heterogeneity and fluid migration. Baffles affecting migration are identified as the shale layers between sand clinoforms and regressive surfaces in the highstand-lowstand systems tracts. Primary trapping surfaces influencing CO2 migration are the regressive surfaces in the transgressive systems tract (TST), where migration pathways converge along common surfaces. Thesesequence stratigraphic observations are then applied to reservoir characterization in 3D seismic data from offshore Gulf of Mexico. The regional, sequence stratigraphic surfaces are well represented in sub-surface data. Hydrocarbon production data indicate fluid accumulation in TST stratigraphy, similar to the geologic modeling results, suggesting some predictability of fluid flow in deltaic settings. The novel integration of datatypes produces enhanced understanding of subsurface fluid flow in deltaic environments.

Download or read book Geologic Controls on Reservor Quality and Geologic Carbon Sequestration Potential in the Upper Cambrian Mount Simon Sandstone written by Kyle Patterson and published by . This book was released on 2011 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Upper (?) Cambrian Mount Simon Standstone is an important deep saline geological carbon sequestration (GCS) target throughout the Midwest, USA. The distribution of sedimentary facies, primary mineralogy, and diagenetic alterations and the relationship to wireline log response and reservoir quality throughout the Michigan basin are not well known. This study uses rock core, thin section points counts, x-ray diffraction, inferred spectoscopy, conventional core plug porosity and permeability and pressure fall-off test data to constrain wierline log interpretations of regional geology and reservoir quality. Prior to the permitting of a CO2 sequestration project, documentation of a robust transient injection model is needed to predict the possible outcomes of CO2 injection. The first step to creating a reliable transient model is creating a sound static geologic model. This study created static geologic models for two locations in Michigan using Schlumberger's Petrel. Gamma ray, wireline log porosity and wireline log estimated permeability were all modeled.

Download or read book Petrophysical Modeling and Simulation Study of Geological CO2 Sequestration written by Xianhui Kong and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global warming and greenhouse gas (GHG) emissions have recently become the significant focus of engineering research. The geological sequestration of greenhouse gases such as carbon dioxide (CO2) is one approach that has been proposed to reduce the greenhouse gas emissions and slow down global warming. Geological sequestration involves the injection of produced CO2 into subsurface formations and trapping the gas through many geological mechanisms, such as structural trapping, capillary trapping, dissolution, and mineralization. While some progress in our understanding of fluid flow in porous media has been made, many petrophysical phenomena, such as multi-phase flow, capillarity, geochemical reactions, geomechanical effect, etc., that occur during geological CO2 sequestration remain inadequately studied and pose a challenge for continued study. It is critical to continue to research on these important issues. Numerical simulators are essential tools to develop a better understanding of the geologic characteristics of brine reservoirs and to build support for future CO2 storage projects. Modeling CO2 injection requires the implementation of multiphase flow model and an Equation of State (EOS) module to compute the dissolution of CO2 in brine and vice versa. In this study, we used the Integrated Parallel Accurate Reservoir Simulator (IPARS) developed at the Center for Subsurface Modeling at The University of Texas at Austin to model the injection process and storage of CO2 in saline aquifers. We developed and implemented new petrophysical models in IPARS, and applied these models to study the process of CO2 sequestration. The research presented in this dissertation is divided into three parts. The first part of the dissertation discusses petrophysical and computational models for the mechanical, geological, petrophysical phenomena occurring during CO2 injection and sequestration. The effectiveness of CO2 storage in saline aquifers is governed by the interplay of capillary, viscous, and buoyancy forces. Recent experimental data reveals the impact of pressure, temperature, and salinity on interfacial tension (IFT) between CO2 and brine. The dependence of CO2-brine relative permeability and capillary pressure on IFT is also clearly evident in published experimental results. Improved understanding of the mechanisms that control the migration and trapping of CO2 in the subsurface is crucial to design future storage projects for long-term, safe containment. We have developed numerical models for CO2 trapping and migration in aquifers, including a compositional flow model, a relative permeability model, a capillary model, an interfacial tension model, and others. The heterogeneities in porosity and permeability are also coupled to the petrophysical models. We have developed and implemented a general relative permeability model that combines the effects of pressure gradient, buoyancy, and capillary pressure in a compositional and parallel simulator. The significance of IFT variations on CO2 migration and trapping is assessed. The variation of residual saturation is modeled based on interfacial tension and trapping number, and a hysteretic trapping model is also presented. The second part of this dissertation is a model validation and sensitivity study using coreflood simulation data derived from laboratory study. The motivation of this study is to gain confidence in the results of the numerical simulator by validating the models and the numerical accuracies using laboratory and field pilot scale results. Published steady state, core-scale CO2/brine displacement results were selected as a reference basis for our numerical study. High-resolution compositional simulations of brine displacement with supercritical CO2 are presented using IPARS. A three-dimensional (3D) numerical model of the Berea sandstone core was constructed using heterogeneous permeability and porosity distributions based on geostatistical data. The measured capillary pressure curve was scaled using the Leverett J-function to include local heterogeneity in the sub-core scale. Simulation results indicate that accurate representation of capillary pressure at sub-core scales is critical. Water drying and the shift in relative permeability had a significant impact on the final CO2 distribution along the core. This study provided insights into the role of heterogeneity in the final CO2 distribution, where a slight variation in porosity gives rise to a large variation in the CO2 saturation distribution. The third part of this study is a simulation study using IPARS for Cranfield pilot CO2 sequestration field test, conducted by the Bureau of Economic Geology (BEG) at The University of Texas at Austin. In this CO2 sequestration project, a total of approximately 2.5 million tons supercritical CO2 was injected into a deep saline aquifer about ~10000 ft deep over 2 years, beginning December 1st 2009. In this chapter, we use the simulation capabilities of IPARS to numerically model the CO2 injection process in Cranfield. We conducted a corresponding history-matching study and got good agreement with field observation. Extensive sensitivity studies were also conducted for CO2 trapping, fluid phase behavior, relative permeability, wettability, gravity and buoyancy, and capillary effects on sequestration. Simulation results are consistent with the observed CO2 breakthrough time at the first observation well. Numerical results are also consistent with bottomhole injection flowing pressure for the first 350 days before the rate increase. The abnormal pressure response with rate increase on day 350 indicates possible geomechanical issues, which can be represented in simulation using an induced fracture near the injection well. The recorded injection well bottomhole pressure data were successfully matched after modeling the fracture in the simulation model. Results also illustrate the importance of using accurate trapping models to predict CO2 immobilization behavior. The impact of CO2/brine relative permeability curves and trapping model on bottom-hole injection pressure is also demonstrated.

Download or read book Integrated Reflection Seismic Monitoring and Reservoir Modeling for Geologic CO2 Sequestration written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The US DOE/NETL CCS MVA program funded a project with Fusion Petroleum Technologies Inc. (now SIGMA) to model the proof of concept of using sparse seismic data in the monitoring of CO2 injected into saline aquifers. The goal of the project was to develop and demonstrate an active source reflection seismic imaging strategy based on deployment of spatially sparse surface seismic arrays. The primary objective was to test the feasibility of sparse seismic array systems to monitor the CO2 plume migration injected into deep saline aquifers. The USDOE/RMOTC Teapot Dome (Wyoming) 3D seismic and reservoir data targeting the Crow Mountain formation was used as a realistic proxy to evaluate the feasibility of the proposed methodology. Though the RMOTC field has been well studied, the Crow Mountain as a saline aquifer has not been studied previously as a CO2 sequestration (storage) candidate reservoir. A full reprocessing of the seismic data from field tapes that included prestack time migration (PSTM) followed by prestack depth migration (PSDM) was performed. A baseline reservoir model was generated from the new imaging results that characterized the faults and horizon surfaces of the Crow Mountain reservoir. The 3D interpretation was integrated with the petrophysical data from available wells and incorporated into a geocellular model. The reservoir structure used in the geocellular model was developed using advanced inversion technologies including Fusion's ThinMAN{trademark} broadband spectral inversion. Seal failure risk was assessed using Fusion's proprietary GEOPRESS{trademark} pore pressure and fracture pressure prediction technology. CO2 injection was simulated into the Crow Mountain with a commercial reservoir simulator. Approximately 1.2MM tons of CO2 was simulated to be injected into the Crow Mountain reservoir over 30 years and subsequently let 'soak' in the reservoir for 970 years. The relatively small plume developed from this injection was observed migrating due to gravity to the apexes of the double anticline in the Crow Mountain reservoir of the Teapot dome. Four models were generated from the reservoir simulation task of the project which included three saturation models representing snapshots at different times during and after simulated CO2 injection and a fully saturated CO2 fluid substitution model. The saturation models were used along with a Gassmann fluid substitution model for CO2 to perform fluid volumetric substitution in the Crow Mountain formation. The fluid substitution resulted in a velocity and density model for the 3D volume at each saturation condition that was used to generate a synthetic seismic survey. FPTI's (Fusion Petroleum Technologies Inc.) proprietary SeisModelPRO{trademark} full acoustic wave equation software was used to simulate acquisition of a 3D seismic survey on the four models over a subset of the field area. The simulated acquisition area included the injection wells and the majority of the simulated plume area.

Download or read book Modeling Oil Production CO2 Injection and Associated Storage in Depleted Oil Reservoirs written by Srikanta Mishra and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Midwest Regional Carbon Sequestration Partnership has been investigating various reservoir characterization and modeling technologies as part of its commercial-scale implementation of carbon dioxide injection for geologic storage in multiple Silurian carbonate pinnacle reefs in northern Michigan, USA. This paper compares multiple reservoir modeling approaches for history-matching oil production and CO2 injection responses, and estimating associated storage, to characterize these small spatial footprint depleted reef reservoirs. The three approaches considered are: fully compositional simulation, black-oil with pseudo-miscibility treatment, and capacitance resistance modeling (CRM). Modeling results from three reefs illustrating each modeling approach are presented, and their applicability and limitations with respect to data needs and modeling objectives are discussed.

Download or read book Numerical Modeling of CO2 Sequestration in Geologic Formations Recent Results and Open Challenges written by Karsten Pruess and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Rising atmospheric concentrations of CO2, and their role inglobal warming, have prompted efforts to reduce emissions of CO2 fromburning of fossil fuels. An attractive mitigation option underconsideration in many countries is the injection of CO2 from stationarysources, such as fossil-fueled power plants, into deep, stable geologicformations, where it would be stored and kept out of the atmosphere fortime periods of hundreds to thousands of years or more. Potentialgeologic storage reservoirs include depleted or depleting oil and gasreservoirs, unmineable coal seams, and saline formations. While oil andgas reservoirs may provide some attractive early targets for CO2 storage, estimates for geographic regions worldwide have suggested that onlysaline formations would provide sufficient storage capacity tosubstantially impact atmospheric releases. This paper will focus on CO2storage in saline formations. Injection of CO2 into a saline aquifer willgive rise to immiscible displacement of brine by the advancing CO2. Thelower viscosity of CO2 relative to aqueous fluids provides a potentialfor hydrodynamic instabilities during the displacement process. Attypical subsurface conditions of temperature and pressure, CO2 is lessdense than aqueous fluids and is subject to upward buoyancy force inenvironments where pressures are controlled by an ambient aqueous phase. Thus CO2 would tend to rise towards the top of a permeable formation andaccumulate beneath the caprock. Some CO2 will also dissolve in theaqueous phase, while the CO2-rich phase may dissolve some formationwaters, which would tend to dry out the vicinity of the injection wells. CO2 will make formation waters more acidic, and will induce chemicalrections that may precipitate and dissolve mineral phases (Xu et al.,2004). As a consequence of CO2 injection, significant pressurization offormation fluids would occur over large areas. These pressurizationeffects will change effective stresses, and may cause movement alongfaults with associated seismicity and increases in permeability thatcould lead to leakage from the storage reservoir (Rutqvist and Tsang,2005).

Download or read book Computational Models for CO2 Geo sequestration Compressed Air Energy Storage written by Rafid Al-Khoury and published by CRC Press. This book was released on 2014-04-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive mathematical and computational modeling of CO2 Geosequestration and Compressed Air Energy StorageEnergy and environment are two interrelated issues of great concern to modern civilization. As the world population will soon reach eight billion, the demand for energy will dramatically increase, intensifying the use of fossil fuels. Ut

Download or read book Data Driven Analytics for the Geological Storage of CO2 written by Shahab D. Mohaghegh and published by CRC Press. This book was released on 2018 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.

Download or read book Model Selection for CO2 Sequestration Using Surface Deflection and Injection Data written by Chiazor Nwachukwu and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, sequestration of CO2 in the subsurface has been studied more extensively as an approach to curb carbon emissions into the atmosphere. Monitoring the fate and migration of the CO2 plume in the aquifer is of utmost interest to regulators and operators. Current monitoring techniques like time-lapse seismic are expensive and have limited applicability. Moreover, these techniques have little predictive value unless embedded within a feedback-style control scheme. Provided that field data such as bottom-hole pressures, well rates, or even surface deformation is available, geologic models for the aquifer can be created and used, as an input to a flow simulator, to predict the migration of CO2. A history matching approach has been developed, within a model selection framework, to select and refine geologic models within a selected set of models until they represent the spatial heterogeneity of the target aquifer, and produce forecast with relatively small uncertainty. An initial large suite of models can be created based on prior information of the aquifer. Predicting the response from these models however, presents a problem in terms of computational time and expense. A particle-tracking algorithm has been developed to estimate the flow response from geologic models, while significantly reducing computational costs. This algorithm serves as a fast approximation of finite-difference flow simulation models, and is meant to provide a rapid estimation of connectivity of the aquifer models. A finite element method (FEM) solver was also developed to approximate the geomechanical effects in the rock caused by the injection of CO2. The approach used here utilizes a partial coupling scheme to sequentially solve the flow and geomechanical equilibrium equations. The validity of the proxies is tested on both 2D and 3D field cases, and the solutions are shown to correlate reasonably well with full-physics simulations. We also demonstrate the application of the model selection algorithm to a 3D reservoir with complex topography. The algorithm includes three main steps: (1) predicting the flow and geomechanical response of a large prior ensemble of models using the proxies; (2) grouping models with similar responses into clusters using multidimensional scaling together with a k-means clustering approach; and (3) selecting a model cluster that produces the minimum deviation from the observed field data. The model selection procedure can be repeated using the sub-group of models within a selected cluster in order to further refine the forecasts for future plume migration. This entire iterative model selection scheme is demonstrated using the injection data for the Krechba reservoir in Algeria, which is an active site for CO2 sequestration.