Model Selection For Co2 Sequestration Using Surface Deflection And Injection Data

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Model Selection for CO2 Sequestration Using Surface Deflection and Injection Data

Author : Chiazor Nwachukwu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (95 download)

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Book Synopsis Model Selection for CO2 Sequestration Using Surface Deflection and Injection Data by : Chiazor Nwachukwu

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.

Geologic Modeling and Data Assimilation for CO2 Sequestration in Point Bar Reservoirs

Author : Ismael Dawuda
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (144 download)

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Book Synopsis Geologic Modeling and Data Assimilation for CO2 Sequestration in Point Bar Reservoirs by : Ismael Dawuda

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.

In-Situ MVA of CO2 Sequestration Using Smart Field Technology

Author :
Publisher :
ISBN 13 :
Total Pages : 323 pages
Book Rating : 4.:/5 (946 download)

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Book Synopsis In-Situ MVA of CO2 Sequestration Using Smart Field Technology by :

Download or read book In-Situ MVA of CO2 Sequestration Using Smart Field Technology written by and published by . This book was released on 2014 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Capability of underground carbon dioxide storage to confine and sustain injected CO2 for a long period of time is the main concern for geologic CO2 sequestration. If a leakage from a geological CO2 sequestration site occurs, it is crucial to find the approximate amount and the location of the leak, in a timely manner, in order to implement proper remediation activities. An overwhelming majority of research and development for storage site monitoring has been concentrated on atmospheric, surface or near surface monitoring of the sequestered CO2 . This study aims to monitor the integrity of CO2 storage at the reservoir level. This work proposes developing in-situ CO2 Monitoring and Verification technology based on the implementation of Permanent Down-hole Gauges (PDG) or "Smart Wells" along with Artificial Intelligence and Data Mining (AI & DM). The technology attempts to identify the characteristics of the CO2 leakage by de-convolving the pressure signals collected from Permanent Down-hole Gauges (PDG). Citronelle field, a saline aquifer reservoir, located in the U.S. was considered as the basis for this study. A reservoir simulation model for CO2 sequestration in the Citronelle field was developed and history matched. PDGs were installed, and therefore were considered in the numerical model, at the injection well and an observation well. Upon completion of the history matching process, high frequency pressure data from PDGs were generated using the history matched numerical model using different CO2 leakage scenarios. Since pressure signal behaviors were too complicated to de-convolute using any existing mathematical formulations, a Machine Learning-based technology was introduced for this purpose. An Intelligent Leakage Detection System (ILDS) was developed as the result of this effort using the machine learning and pattern recognition technologies. The ILDS is able to detect leakage characteristics in a short period of time (less than a day from its occurrence) demonstrating the capability of the system in quantifying leakage characteristics subject to complex rate behaviors. The performance of ILDS is examined under different conditions such as multiple well leakages, cap rock leakage, availability of an additional monitoring well, presence of pressure drift and noise in the pressure sensor and uncertainty in the reservoir model.

Predicting the Migration of CO2 Plume in Saline Aquifers Using Probabilistic History Matching Approaches

Author : Sayantan Bhowmik
Publisher :
ISBN 13 :
Total Pages : 154 pages
Book Rating : 4.:/5 (86 download)

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Book Synopsis Predicting the Migration of CO2 Plume in Saline Aquifers Using Probabilistic History Matching Approaches by : Sayantan Bhowmik

Download or read book Predicting the Migration of CO2 Plume in Saline Aquifers Using Probabilistic History Matching Approaches written by Sayantan Bhowmik and published by . This book was released on 2012 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the operation of a geological carbon storage project, verifying that the CO2 plume remains within the permitted zone is of particular interest both to regulators and to operators. However, the cost of many monitoring technologies, such as time-lapse seismic, limits their application. For adequate predictions of plume migration, proper representation of heterogeneous permeability fields is imperative. Previous work has shown that injection data (pressures, rates) from wells might provide a means of characterizing complex permeability fields in saline aquifers. Thus, given that injection data are readily available and inexpensive, they might provide an inexpensive alternative for monitoring; combined with a flow model like the one developed in this work, these data could even be used for predicting plume migration. These predictions of plume migration pathways can then be compared to field observations like time-lapse seismic or satellite measurements of surface-deformation, to ensure the containment of the injected CO2 within the storage area. In this work, two novel methods for creating heterogeneous permeability fields constrained by injection data are demonstrated. The first method is an implementation of a probabilistic history matching algorithm to create models of the aquifer for predicting the movement of the CO2 plume. The geologic property of interest, for example hydraulic conductivity, is updated conditioned to geological information and injection pressures. The resultant aquifer model which is geologically consistent can be used to reliably predict the movement of the CO2 plume in the subsurface. The second method is a model selection algorithm that refines an initial suite of subsurface models representing the prior uncertainty to create a posterior set of subsurface models that reflect injection performance consistent with that observed. Such posterior models can be used to represent uncertainty in the future migration of the CO2 plume. The applicability of both methods is demonstrated using a field data set from central Algeria.

Modeling the Dynamics of Carbon Sequestration

Author : Erik James Huber
Publisher :
ISBN 13 :
Total Pages : 546 pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis Modeling the Dynamics of Carbon Sequestration by : Erik James Huber

Download or read book Modeling the Dynamics of Carbon Sequestration written by Erik James Huber and published by . This book was released on 2017 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon sequestration involves capturing CO2 from an exhaust source, compressing it to a supercritical fluid state, and injecting it underground where it can be stored. The environmental engineering goal of carbon sequestration is to prevent further increases in atmospheric CO2 concentration levels. This dissertation examines three aspects of carbon sequestration pertaining to the fluid dynamics of injection and post-injection within the geologic subsurface. First, a time dependent injection strategy of brine alternating with CO2 is proposed as a method to reduce the CO2 mobility by increasing the rates of residual trapping and dissolution. After making some assumptions, the equations governing the dynamics of CO2 mass transport become a coupled set of 1D wave equations, whose wave speeds provide insight into the relative permeability conditions required for this injection strategy to be most effective. Numerical solutions using the method of characteristics are then compared against 3D TOUGH2 simulations and comparable favorably to one another. Both models predict that alternating brine injection can reduce the mass fraction of mobile CO2 to less than 10% using a volume ratio brine:CO2 of less than 2.75 and on time scales that are 100 – 10,000 times faster than would occur with a continuous injection of CO2. Second, the stability of residually trapped CO2 is analyzed with respect to its susceptibility to become remobilized. Here, a reservoir containing a region of homogeneously dispersed pockets of residually trapped CO2 is considered. Should the pore pressure decrease, the CO2 will expand, remobilize, rise within the domain, and potentially spread along the caprock of the formation. The dynamics of this process are predicted using two different relative permeability models: Brooks-Corey, and a modified Brooks-Corey that incorporates percolation theory. Experimental data justifying this latter model is presented. More importantly, the time scales of remobilized CO2 motion are shown to be vastly different for these two models and suggest the need for further experimental data. Finally, as dry CO2 is injected into brine occupied reservoirs, there exists the potential for mechanical tension forces to be generated within the brine which can cause cavitation to occur. These cavitation dynamics are modeled here using explicit and averaged equations and compared to experimental data from drying an idealized synthetic heterogeneous porous media.

Simplified Predictive Models for CO2 Sequestration Performance Assessment

Author :
Publisher :
ISBN 13 :
Total Pages : 102 pages
Book Rating : 4.:/5 (946 download)

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Book Synopsis Simplified Predictive Models for CO2 Sequestration Performance Assessment by :

Download or read book Simplified Predictive Models for CO2 Sequestration Performance Assessment written by and published by . This book was released on 2015 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical "proxy models" are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems - which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

Simplified Predictive Models for CO2 Sequestration Performance Assessment Research Topical Report on Task #3 Statistical Learning Based Models

Download Simplified Predictive Models for CO2 Sequestration Performance Assessment Research Topical Report on Task #3 Statistical Learning Based Models PDF Online Free

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (94 download)

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Book Synopsis Simplified Predictive Models for CO2 Sequestration Performance Assessment Research Topical Report on Task #3 Statistical Learning Based Models by :

Download or read book Simplified Predictive Models for CO2 Sequestration Performance Assessment Research Topical Report on Task #3 Statistical Learning Based Models written by and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We compare two approaches for building a statistical proxy model (metamodel) for CO2 geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO2 injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO2 plume radius and average reservoir pressure. The Box-Behnken-quadratic polynomial metamodel performed the best, followed closely by the maximin LHS-kriging metamodel.

Strategies for Mitigating Risks of Scalibility and Containment in Geological CO2 Storage

Author : Yun Wu (Ph. D.)
Publisher :
ISBN 13 :
Total Pages : 225 pages
Book Rating : 4.:/5 (13 download)

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Book Synopsis Strategies for Mitigating Risks of Scalibility and Containment in Geological CO2 Storage by : Yun Wu (Ph. D.)

Download or read book Strategies for Mitigating Risks of Scalibility and Containment in Geological CO2 Storage written by Yun Wu (Ph. D.) and published by . This book was released on 2017 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: To be relevant for greenhouse gas mitigation, geological CO2 storage in a deep saline aquifer must be scalable, and the stored CO2 must be securely contained. Conventional approaches to aquifer storage have both scalability and containment risks. In this work, the scalability risks of interest are the achievable sustained injection rates of CO2 and storage efficiencies. The containment risks examined here are associated with uncontrolled fracture initiation and propagation in the injection zone, and CO2 leakage. Operational strategies for minimizing the risks of scalability and containment while maximizing the injection rate and storage efficiency are important to support commercially viable implementations of numerous large-scale CO2 storage projects. We focus on the CO2 storage by surface dissolution strategy, which stores the captured CO2 in a storage aquifer by dissolving it into brine extracted from the storage formation and then injecting CO2-saturated brine into the same storage formation. This method has advantages over the standard CO2 storage method in eliminating or reducing certain containment risks, but it still faces the scalability risks of achieving large injection rates. We quantify the maximum injection rate of CO2-saturated brine for a safe storage project, by preventing the initiation and propagation of tensile fractures. We incorporate thermal constraints in our model by including the induced thermoelastic stress in the calculation of the formation breakdown pressure. We design a closed-loop surface dissolution technique that completely eliminates the problem of brine disposal. However, when using this technique the buildup of reservoir pressure gradually reduces the maximum injection rate. We propose a strategy to manage the pressure distribution and maximize the injection rates for each injector. Yet in large-scale geological CO2 storage projects, injection-induced fracturing may be unavoidable when injecting at desired rates. We develop models to analyze injection data from a field supercritical CO2 injection project. The analysis suggests that proper pressure management could stop the propagation of injection-induced fractures. This self-limiting feature of injection-induced fracturing mitigates the containment risks and greatly increases the injection rates. To improve the aquifer utilization efficiency for CO2 storage using the surface dissolution strategy, we continue injecting CO2-saturated brine beyond the pressure contour corresponding to the bubble point. However, this introduces the risks of CO2 leakage. We develop a 1D model in a homogeneous aquifer to study the migration of two-phase fluid flow. Two limiting cases are studied to confine the mobility of free gaseous phase. The results indicate a significant increase in stored CO2 with low risks of leakage because of the small saturation and mobility of exsolved CO2. Allowing the breakthrough of injected CO2-saturated brine at the producers would also increase the aquifer utilization efficiency. The aquifer utilization efficiency can be optimized by minimizing the production/recycling rate of CO2-saturated brine in heterogeneous fields. The results show greatly improved aquifer utilization efficiencies at the cost of handling a small pore volume of produced/recycled CO2-saturated brine.

Petrophysical Modeling and Simulation Study of Geological CO2 Sequestration

Author : Xianhui Kong
Publisher :
ISBN 13 :
Total Pages : 452 pages
Book Rating : 4.:/5 (881 download)

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Book Synopsis Petrophysical Modeling and Simulation Study of Geological CO2 Sequestration by : Xianhui Kong

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 452 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.

Modeling CO2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas

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ISBN 13 :
Total Pages : 1000 pages
Book Rating : 4.:/5 (957 download)

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Book Synopsis Modeling CO2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas by :

Download or read book Modeling CO2 Sequestration in Saline Aquifer and Depleted Oil Reservoir To Evaluate Regional CO2 Sequestration Potential of Ozark Plateau Aquifer System, South-Central Kansas written by and published by . This book was released on 2014 with total page 1000 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Drilled, cored, and logged three wells to the basement and collecting more than 2,700 ft of conventional core; obtained 20 mi2 of multicomponent 3D seismic imaging and merged and reprocessed more than 125 mi2 of existing 3D seismic data for use in modeling CO2- EOR oil recovery and CO2 storage in five oil fields in southern Kansas. 2. Determined the technical feasibility of injecting and sequestering CO2 in a set of four depleted oil reservoirs in the Cutter, Pleasant Prairie South, Eubank, and Shuck fields in southwest Kansas; of concurrently recovering oil from those fields; and of quantifying the volumes of CO2 sequestered and oil recovered during the process. 3. Formed a consortium of six oil operating companies, five of which own and operate the four fields. The consortium became part of the Southwest Kansas CO2-EOR Initiative for the purpose of sharing data, knowledge, and interest in understanding the potential for CO2-EOR in Kansas. 4. Built a regional well database covering 30,000 mi2 and containing stratigraphic tops from ~90,000 wells; correlated 30 major stratigraphic horizons; digitized key wells, including wireline logs and sample logs; and analyzed more than 3,000 drill stem tests to establish that fluid levels in deep aquifers below the Permian evaporites are not connected to the surface and therefore pressures are not hydrostatic. Connectivity with the surface aquifers is lacking because shale aquitards and impermeable evaporite layers consist of both halite and anhydrite. 5. Developed extensive web applications and an interactive mapping system that do the following: a. Facilitate access to a wide array of data obtained in the study, including core descriptions and analyses, sample logs, digital (LAS) well logs, seismic data, gravity and magnetics maps, structural and stratigraphic maps, inferred fault traces, earthquakes, Class I and II disposal wells, and surface lineaments. b. Provide real-time analysis of the project dataset, including automated integration and viewing of well logs, core, core analyses, brine chemistry, and stratigraphy using the Java Profile app. A cross-section app allows for the display of log data for up to four wells at a time. 6. Integrated interpretations from the project's interactive web-based mapping system to gain insights to aid in assessing the efficacy of geologic CO2 storage in Kansas and insights toward understanding recent seismicity to aid in evaluating induced vs. naturally occurring earthquakes. 7. Developed a digital type-log system, including web-based software to modify and refine stratigraphic nomenclature to provide stakeholders a common means for communication about the subsurface. 8. Contracted use of a nuclear magnetic resonance (NMR) log and ran it slowly to capture response and characterize larger pores common for carbonate reservoirs. Used NMR to extend core analyses to apply permeability, relative permeability to CO2, and capillary pressure to the major rock types, each uniquely expressed as a reservoir quality index (RQI), present in the Mississippian and Arbuckle rocks. 9. Characterized and evaluated the possible role of microbes in dense brines. Used microbes to compliment H/O stable isotopes to fingerprint brine systems. Used perforation/swabbing to obtain samples from multiple hydrostratigraphic units and confirmed equivalent results using less expensive drill stem tests (DST). 10. Used an integrated approach from whole core, logs, tests, and seismic to verify and quantify properties of vuggy, brecciated, and fractured carbonate intervals. 11. Used complex geocellular static and dynamic models to evaluate regional storage capacity using large parallel processing. 12. Carbonates are complex reservoirs and CO2-EOR needs to move to the next generation to increase effectiveness of CO2 and efficiency and safety of the inj ...

Geological Storage of CO2

Author : Jan Martin Nordbotten
Publisher : Wiley
ISBN 13 : 9781118137062
Total Pages : 0 pages
Book Rating : 4.1/5 (37 download)

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Book Synopsis Geological Storage of CO2 by : Jan Martin Nordbotten

Download or read book Geological Storage of CO2 written by Jan Martin Nordbotten and published by Wiley. This book was released on 2011-10-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite the large research effort in both public and commercial companies, no textbook has yet been written on this subject. This book aims to provide an overview to the topic of Carbon Capture and Storage (CSS), while at the same time focusing on the dominant processes and the mathematical and numerical methods that need to be employed in order to analyze the relevant systems. The book clearly states the carbon problem and the role of CCS and carbon storage. Thereafter, it provides an introduction to single phase and multi-phase flow in porous media, including some of the most common mathematical analysis and an overview of numerical methods for the equations. A considerable part of the book discusses the appropriate scales of modeling, and how to formulate consistent governing equations at these scales. The book also illustrates real world data sets and how the ideas in the book can be exploited through combinations of analytical and numerical approaches.

Carbon Sequestration

Author : Mirhamed Sarkarfarshi
Publisher :
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (946 download)

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Book Synopsis Carbon Sequestration by : Mirhamed Sarkarfarshi

Download or read book Carbon Sequestration written by Mirhamed Sarkarfarshi and published by . This book was released on 2015 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carbon Capture and Sequestration (CCS) appears to be a practical technology for large-scale storage of CO2 to reduce anthropogenic CO2 emissions. Risk is an inevitable component of any geological project with the aim of storing CO2, and thus, is a concern to the public, policy makers, and scientists. Uncertainty that arises in the application of mathematical Carbon Sequestration (CS) models has a negative impact on the quality of risk assessment. Parameter uncertainty is believed to play a dominant role in the uncertainty of the outputs of the CS system models. However, reducing parameter uncertainty in CS models involves a trade-off between accuracy and computational efficiency of the model calibration methodology. The goal of this thesis is to reduce the trade-off between accuracy and computational efficiency when calibrating CS models. This is accomplished by, one, reducing the dimensionality of the parameter space; two, developing efficient calibration algorithms; and, three, reducing the computational cost of model simulation during calibration. The primary contributions of this thesis are: 1. The development of a sensitivity analysis to identify which parameters contribute the most to the uncertainty of the CS system model output, accounting for both parameter uncertainty and model structure. 2. The development of a computationally efficient and flexible Bayesian Importance Sampling (IS) method for continuous calibration of CS models using noisy monitoring data collected during the injection phase. 3. The development of the Response Surface Methodology (RSM) in a novel adaptive way to mitigate the computational demand of CS model calibration with negligible effect on the accuracy of the results. The methodologies and results presented in this thesis contribute to efficient calibration of CS models by identifying the most influential parameters in uncertainty of CS model outputs and calibrating those models accurately and efficiently.

CO2 Storage in Deltaic Environments of Deposition

Author : Emily Christine Beckham
Publisher :
ISBN 13 :
Total Pages : 402 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis CO2 Storage in Deltaic Environments of Deposition by : Emily Christine Beckham

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.

Modeling CO2 Leakage from Geological Storage Formation and Reducing the Associated Risk

Author : Qing Tao (Ph. D.)
Publisher :
ISBN 13 :
Total Pages : 384 pages
Book Rating : 4.:/5 (818 download)

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Book Synopsis Modeling CO2 Leakage from Geological Storage Formation and Reducing the Associated Risk by : Qing Tao (Ph. D.)

Download or read book Modeling CO2 Leakage from Geological Storage Formation and Reducing the Associated Risk written by Qing Tao (Ph. D.) and published by . This book was released on 2012 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large-scale geological storage of CO2 is likely to bring CO2 plumes into contact with existing wellbores and faults, which can act as pathways for leakage of stored CO2 Modeling the flux of CO2 along a leaky pathway requires transport properties along the pathway. We provide an approach based on the analogy between the leakage pathway in wells that exhibit sustained casing pressure (SCP) and the rate-limiting part of the leakage pathway in any wellbore that CO2 might encounter. By using field observations of SCP to estimate transport properties of a CO2 leakage pathway, we obtain a range of CO2 fluxes for the cases of buoyancy-driven (post-injection) and pressure-driven (during injection) leakage. The fluxes in example wells range from background levels to three orders of magnitude higher than flux at the natural CO2 seep in Crystal Geyser, Utah. We estimate a plausible range of fault properties from field data in the Mahogany Field using a shale gouge ratio correlation. The estimated worst-case CO2 flux is slightly above background range. The flux along fault could be attenuated to zero by permeable layers that intersect the fault. The attenuation is temporary if layers are sealed at other end. Counterintuitively, greater elevation in pressure at the base of the fault can result in less CO2 leakage at the top of the fault, because the capillary entry pressure is exceeded for more permeable layers. Since non-negligible leakage rates are possible along wellbores, it is important to be able to diagnose whether leakage is occurring. Concurrent pressure and temperature measurements are especially valuable because they independently constrain the effective permeability of a leakage path along wellbore. We describe a simple set of coupled analytical models that enable diagnosis of above-zone monitoring data. Application to data from a monitoring well during two years of steady CO2 injection shows that the observed pressure elevation requires a model with an extremely large leakage rate, while the temperature model shows that this rate would be large enough to raise the temperature in the monitoring zone significantly, which is not observed. The observation well is unlikely to be leaking. Extraction of brine from the aquifer offers advantage over standard storage procedure by greatly mitigating pressure elevation during CO2 injection. A proper management of the injection process helps reduce the risk of leakage associated with wellbores and faults. We provide strategies that optimize the injection of CO2 which involve extraction of brine in two scenarios, namely injecting dissolved CO2 and supercritical CO2. For surface dissolution case we are concerned with bubble point contour, while for supercritical CO2 injection we are concerned with breakthrough of CO2 at extractors. In a surface dissolution project, the CO2 concentration front shape when it reaches the saturation pressure contour defines the maximum areal extent of CO2-saturated brine and hence the aquifer utilization efficiency. We illustrate the reduction of utilization efficiency due to heterogeneity of the aquifer. We develop an optimal control strategy of the injection/extraction rates to maximize the utilization efficiency. We further propose an optimal well pattern orientation strategy. Results show that the approach nearly compensates the reduction of utilization efficiency due to heterogeneity. In a supercritical CO2 injection that involves brine extraction, the problem of avoiding breakthrough of CO2 at extraction wells can be addressed by optimizing flow rates at each extractor and injector to delay breakthrough as long as possible. We use the Capacitance-Resistive Model (CRM) to conduct the optimization. CRM runs rapidly and requires no prior geologic model. Fitting the model to data recorded during early stages of CO2 injection characterizes the connectivities between injection and brine-extraction wells. The fitted model parameters are used to optimize subsequent CO2 injection in the formation. Field illustration shows a significant improvement in CO2 storage efficiency.

Investigating the Geochemical Alterations in an Aquifer Due to Long-term Sequestration of CO2 Using Time-lapse Seismic Information

Author : Sang Hyon Han
Publisher :
ISBN 13 :
Total Pages : 176 pages
Book Rating : 4.:/5 (943 download)

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Book Synopsis Investigating the Geochemical Alterations in an Aquifer Due to Long-term Sequestration of CO2 Using Time-lapse Seismic Information by : Sang Hyon Han

Download or read book Investigating the Geochemical Alterations in an Aquifer Due to Long-term Sequestration of CO2 Using Time-lapse Seismic Information written by Sang Hyon Han and published by . This book was released on 2015 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: The effects of chemical interaction between injected CO2, brine, and formation rocks are often ignored in sequestration studies because chemical reactions are assumed to be localized to carbonate rocks that make up only a small proportion of the potential reservoirs. It is conjectured in this work that long-term exposure of certain types of clays and cement material to CO2-brine mixtures can induce chemical reactions and subsequent alteration of rock properties that can be subsequently detected in time-lapse seismic surveys. This is demonstrated using a case-study structured after the Cranfield field injection site. Geochemical alterations of the reservoir rock are quantified by performing reactive transport simulations and subsequently using rock physics models to translate the altered petrophysical properties into seismic responses. The study quantifies the long-term geochemical effects of CO2 injection on the seismic response and conversely, presents an approach to invert the reservoir regions contacted by the CO2-saturated brine based on the observed seismic response. Time lapse or passive seismic monitoring is an effective method for mapping the progress of the CO2 plume through the subsurface. But, because of the lack of resolution of the seismic information, it is necessary to use the seismic information together with prior geologic knowledge about the surface in order to identify if there is any migration of CO2 into regions that might be deemed sensitive e.g. overlying aquifers or faults. Because of uncertainties in the prior geologic description of the reservoir, the feasibility of implementing a model selection process is explored in this work. The model selection procedure utilizes the observed well data and reference seismic map to select a subset of models. The flow simulation of CO2 injection and forward seismic modeling were repeated for the newly generated reservoir models, and the seismic responses were compared for the reaction and non-reaction cases. The study showed that the effects of geochemical reactions on petrophysical properties and resultant spatial distribution of fluid saturation were visible in the seismic response. Major differences in seismic responses were detected in regions of the reservoir where significant amount of minerals were dissolved and precipitated. These regions were at the top of the reservoir due to the reactions caused by the buoyant CO2 plume. The presence of carbonate facies, even in small proportion, plays an important role in geochemical reactions and their effect is manifested at the seismic scale. The unique model selection methodology presented in this thesis is efficient at detecting the important features in the seismic and injection response that is induced by the geochemical alterations occurring in the reservoir. The results of this time-lapse study can provide new interpretation of events observed in time-lapse seismic data that might lead to a better assessment of leakage pathways and other risks.

An Uncertainty Analysis of Modeling Geologic Carbon Sequestration in a Naturally Fractured Reservoir at Teapot Dome, Wyoming

Author : Ye Li
Publisher :
ISBN 13 : 9781321174526
Total Pages : 198 pages
Book Rating : 4.1/5 (745 download)

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Book Synopsis An Uncertainty Analysis of Modeling Geologic Carbon Sequestration in a Naturally Fractured Reservoir at Teapot Dome, Wyoming by : Ye Li

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.

Particle Tracking Proxies for Prediction of CO2 Plume Migration Within a Model Selection Framework

Author : Sayantan Bhowmik
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (885 download)

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Book Synopsis Particle Tracking Proxies for Prediction of CO2 Plume Migration Within a Model Selection Framework by : Sayantan Bhowmik

Download or read book Particle Tracking Proxies for Prediction of CO2 Plume Migration Within a Model Selection Framework written by Sayantan Bhowmik and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geologic sequestration of CO2 in deep saline aquifers has been studied extensively over the past two decades as a viable method of reducing anthropological carbon emissions. The monitoring and prediction of the movement of injected CO2 is important for assessing containment of the gas within the storage volume, and taking corrective measures if required. Given the uncertainty in geologic architecture of the storage aquifers, it is reasonable to depict our prior knowledge of the project area using a vast suite of aquifer models. Simulating such a large number of models using traditional numerical flow simulators to evaluate uncertainty is computationally expensive. A novel stochastic workflow for characterizing the plume migration, based on a model selection algorithm developed by Mantilla in 2011, has been implemented. The approach includes four main steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models using proxies; (2) model clustering using the principle component analysis or multidimensional scaling coupled with the k-mean clustering approach; (3) model selection using the Bayes' rule on the reduced model space, and (4) model expansion using an ensemble pattern-based matching scheme. In this dissertation, two proxies have been developed based on particle tracking in order to assess the flow connectivity of models in the initial set. The proxies serve as fast approximations of finite-difference flow simulation models, and are meant to provide rapid estimations of connectivity of the aquifer models. Modifications have also been implemented within the model selection workflow to accommodate the particular problem of application to a carbon sequestration project. The applicability of the proxies is tested both on synthetic models and real field case studies. It is demonstrated that the first proxy captures areal migration to a reasonable extent, while failing to adequately capture vertical buoyancy-driven flow of CO2. This limitation of the proxy is addressed in the second proxy, and its applicability is demonstrated not only in capturing horizontal migration but also in buoyancy-driven flow. Both proxies are tested both as standalone approximations of numerical simulation and within the larger model selection framework.