Download or read book Joint Integration of Time lapse Seismic Electromagnetic and Production Data for Reservoir Monitoring and Management written by Jaehoon Lee and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Joint integration of time-lapse seismic, time-lapse electromagnetic, and production data can provide a powerful means of characterizing and monitoring reservoirs. Those data contain complementary information about the changes in the reservoir during operation, and, thus, their proper integration can lead to more reliable forecasts and optimal decisions in reservoir management. This dissertation focuses on developing workflows to jointly integrate time-lapse seismic, electromagnetic, and production data because this task is significantly time-consuming and very challenging. The first part of the thesis addresses a quick and efficient method, which can provide a tool for locating the changes in the reservoir and assessing the uncertainty associated with the estimation quantitatively. The developed workflow, termed statistical integration workflow, utilizes well logs to link reservoir properties with seismic and electromagnetic data by building the joint probability distribution. A new upscaling method from well logs to the scales of seismic and electromagnetic measurements is established using multiple-point geostatistical simulation. The statistical integration workflow is applied to facies classification and the detection of depleted regions. Stochastic optimization is also investigated in this dissertation. As the joint optimization of time-lapse seismic, electromagnetic, and production data requires a huge amount of computational time, we formulate a new algorithm, the probabilistic particle swarm optimization (Pro-PSO). This algorithm is designed to alleviate the time-consuming job by parallel computations of multiple candidate models and the improvement of models based on information sharing. More importantly, any probabilistic priors, such as geological information, can be incorporated into the algorithm. Applications are investigated for a synthetic example of seismic inversion and flow history matching of a Gaussian porosity field, parameterized by its spatial principal components. The result validates the effectiveness of Pro-PSO as compared with conventional PSO. Another version of Pro-PSO for discrete parameters, called Pro-DPSO, is also developed where particles (candidate models) move in the probability mass function space instead of the parameter space. Then, Pro-DPSO is hybridized with a multiple-point geostatistical algorithm, the single normal equation algorithm (SNESIM) to preserve non-Gaussian geological features. This hybridized algorithm (Pro-DPSO-SNESIM) is evaluated on a synthetic example of seismic inversion and compared with a Markov chain Monte Carlo (MCMC) optimization method. The algorithms Pro-DPSO and Pro-DPSO-SNESIM provide not only optimized models but also optimized probability mass functions (pmf) of parameters. Therefore, it also presents the variations of realizations sampled from the optimized pmfs. Lastly, we introduce the specialization workflow of Pro-PSO algorithms for the joint integration of time-lapse seismic, time-lapse electromagnetic, and production data. In this workflow, the particles of Pro-PSO are divided into several groups, and each group is specialized in the evaluation of a particular type of data misfit. Dividing up the objective function components among different groups of particles allows the algorithm to take advantage of situations where different forward simulators for each type of data require very different computational times per iteration. The optimization is implemented by sharing multiple best models from each type of data misfit, not by sharing a single best model based on the sum (or other combinations) of all the misfits. The "divide-and-conquer" workflow is evaluated on two synthetic cases of joint integration showing that it is much more efficient than an equivalent conventional workflow minimizing an integrated objective function.

Download or read book Practical Applications of Time lapse Seismic Data written by David H. Johnston and published by SEG Books. This book was released on 2013 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse (4D) seismic technology is a key enabler for improved hydrocarbon recovery and more cost-effective field operations. This book shows how 4D data are used for reservoir surveillance, add value to reservoir management, and provide valuable insight on dynamic reservoir properties such as fluid saturation, pressure, and temperature.

Download or read book Joint Inversion of Production and Time lapse Seismic Data written by Amit Suman and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse seismic has evolved as an important diagnostic tool in efficient reservoir characterization and monitoring. Reservoir models, optimally constrained to seismic response, as well as flow response, can provide a better description of the reservoir and thus more reliable forecast. This dissertation focuses on different aspects of joint inversion of time-lapse seismic and production data for reservoir model updating, with application to the Norne field in the Norwegian Sea. This work describes a methodology for joint inversion of production and time-lapse seismic data, analyzes sensitive parameters in the joint inversion, identifies sensitive rock physics parameters for modeling time-lapse seismic response of a field and successfully applies and compares the family of particle swarm optimizers for joint inversion of production and time-lapse seismic data of the Norne field. The contributions from this research include a systematic workflow for joint inversion of time-lapse seismic and production data that can be and has been practically applied to a real field. Better reservoir models, constrained to both data will in turn lead to better reservoir forecasts and better field management. The first part of this thesis uses Norne field data to analyze sensitive parameters in joint inversion of production and time-lapse seismic data. An experimental design is performed on the parameters of the reservoir and seismic simulator. The results are used to rank the parameters in terms of sensitivity to production and time-lapse seismic data. At the same time it is shown that porosity/permeability models is not the most sensitive parameter for joint inversion of production and time-lapse seismic data of the Norne field. The parameters selected for study are porosity and permeability model, relative permeability, rock physics models, pore compressibility and fluid mixing. Results show that rock physics model has the most impact on time-lapse seismic whereas relative permeability is the most important parameter for production response. The results of this study are used in selecting the most important reservoir parameters for joint inversion of time-lapse seismic and production data of the Norne field. It is established that rock physics model is the most sensitive parameter for modeling time-lapse seismic of the Norne field, but there are rock physics parameters associated with rock physics model that impact time-lapse seismic modeling. So it is necessary to identify sensitive rock physics parameters for modeling time-lapse seismic response. Thus, the second part of this thesis identifies sensitive rock physics parameters in modeling time-lapse seismic response of Norne field. At first facies are classified based on well log data. Then sensitive parameters are investigated in the Gassmann's equation to generate the initial seismic velocities. The investigated parameters include mineral properties, water salinity, pore-pressure and gas-oil ratio (GOR). Next, parameter sensitivity for time-lapse seismic modeling of the Norne field is investigated. The investigated rock physics parameters are clay content, cement, pore-pressure and mixing. This sensitivity analysis helps to select important parameters for time-lapse (4D) seismic history matching which is an important aspect of joint inversion of production and time-lapse seismic of a field. Joint inversion of seismic and flow data for reservoir parameter is highly non-linear and complex. Local optimization methods may fail to obtain multiple history matched models. Recently stochastic optimization based inversion has shown very good results in the integration of time-lapse seismic and production data in reservoir history matching. Also, high dimensionality of the inverse problem makes the joint inversion of both data sets computationally expensive. High dimensionality of the inverse problem can be solved by using reduced order models. In this study, principal component bases derived from the prior is used to accomplish this. In the third part of the dissertation a family of particle swarm optimizers is used in combination with principal component bases for inversion of a synthetic data set. The performance of the different particle swarm optimizers is analyzed, both in terms of the quality of history match and convergence rate. Results show that particle swarm optimizers have very good convergence rate for a synthetic case. Also, these optimizers are used in combination with multi-dimensional scaling (MDS) to provide a set of porosity models whose simulated production and time-lapse seismic responses provide satisfactory match with the observed production and time-lapse seismic data. The goal of the last part is to apply the results of previous parts in joint inversion of production and time-lapse seismic data of the Norne field. Time-lapse seismic and production data of the Norne field is jointly inverted by varying the sensitive parameters identified in previous chapters and using different particle swarm optimizers. At first the time-lapse seismic surveys of the Norne field acquired in 2001 and 2004 is quantitatively interpreted and analyzed. Water was injected in the oil and gas producing Norne reservoir and repeat seismic surveys were conducted to monitor the subsurface fluids. The interpreted P-wave impedance change between 2001 and 2004 is used in the joint inversion loop as time-lapse seismic data. The application of different particle swarm optimizers provides a set of parameters whose simulated responses provide a satisfactory history match with the production and time-lapse seismic data of Norne field. It is shown that particle swarm optimizers have potential to be applied for joint inversion of the production and time-lapse seismic data of a real field data set.

Download or read book Time lapse Seismic in Reservoir Management written by Ian Jack and published by . This book was released on 1997 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Detection of Production induced Time lapse Signatures by Geophysical seismic and CSEM Measurements written by Alireza Shahin and published by . This book was released on 2011 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: While geophysical reservoir characterization has been an area of research for the last three decades, geophysical reservoir monitoring, time-lapse studies, have recently become an important geophysical application. Generally speaking, the main target is to detect, estimate, and discriminate the changes in subsurface rock properties due to production. This research develops various sensitivity and feasibility analyses to investigate the effects of production-induced time-lapse changes on geophysical measurements including seismic and controlled-source electromagnetic (CSEM) data. For doing so, a realistic reservoir model is numerically simulated based on a prograding near-shore sandstone reservoir. To account for the spatial distribution of petrophysical properties, an effective porosity model is first simulated by Gaussian geostatistics. Dispersed clay and dual water models are then efficiently combined with other well-known theoretical and experimental petrophysical correlations to consistently simulate reservoir model parameters. Next, the constructed reservoir model is subjected to numerical simulation of multi-phase fluid flow to replicate a waterflooding scenario of a black oil reservoir and to predict the spatial distributions of fluid pressure and saturation. A modified Archie's equation for shaly sandstones is utilized to simulate rock resistivity. Finally, a geologically consistent stress-sensitive rock physics model, combined with the modified Gassmann theory for shaly sandstones, is utilized to simulate seismic elastic parameters. As a result, the comprehensive petro-electro-elastic model developed in this dissertation can be efficiently utilized in sensitivity and feasibility analyses of seismic/CSEM data with respect to petrophysical properties and, ultimately, applied to reservoir characterization and monitoring research. Using the resistivity models, a base and two monitor time-lapse CSEM surveys are simulated via accurate numerical algorithms. 2.5D CSEM modeling demonstrates that a detectable time-lapse signal after 5 years and a strong time-lapse signal after 10 years of waterflooding are attainable with the careful application of currently available CSEM technology. To simulate seismic waves, I employ different seismic modeling algorithms, one-dimensional (1D) acoustic and elastic ray tracing, 1D full elastic reflectivity, 2D split-step Fourier plane-wave (SFPW), and 2D stagger grid explicit finite difference (FD). My analyses demonstrate that acoustic modeling of an elastic medium is a good approximation up to ray parameter (p) equal to 0.2 sec/km. However, at p=0.3 sec/km, differences between elastic and acoustic wave propagation is the more dominant effect compared to internal multiples. Here, converted waves are also generated with significant amplitudes compared to primaries and internal multiples. I also show that time-lapse modeling of the reservoir using SFPW approach is very fast compared to FD, 100 times faster for my case here. It is capable of handling higher frequencies than FD. It provides an accurate image of the waterflooding process comparable to FD. Consequently, it is a powerful alternative for time-lapse seismic modeling. I conclude that both seismic and CSEM data have adequate but different sensitivities to changes in reservoir properties and therefore have the potential to quantitatively map production-induced time-lapse changes.

Download or read book Practical Applications of Time lapse Seismic Data written by David Hervey Johnston and published by . This book was released on 2013 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse (4D) seismic technology is a key enabler for improved hydrocarbon recovery and more cost-effective field operations. Practical Applications of Time-lapse Seismic Data (SEG Distinguished Instructor Series No. 16) shows how 4D seismic data are used for reservoir surveillance, how they provide valuable insight on dynamic reservoir properties such as fluid saturation, pressure, and temperature, and how they add value to reservoir management. The material, based on the 2013 SEG Distinguished Instructor Short Course, includes discussions of reservoir-engineering concepts and rock physics critical to the understanding of 4D data, along with topics in 4D seismic acquisition and processing. A primary focus of the book is interpretation and data integration. Case-study examples are used to demonstrate key concepts and are drawn on to demonstrate the range of interpretation methods currently employed by industry and the diversity of geologic settings and production scenarios in which 4D is making a difference. Time-lapse seismic interpretation is inherently integrative, drawing on geophysical, geologic, and reservoir-engineering data and concepts. As a result, this book should be of interest to individuals from all subsurface disciplines.

Download or read book Fast History Matching of Time lapse Seismic and Production Data for High Resolution Models written by Eduardo Antonio Jimenez and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrated reservoir modeling has become an important part of day-to-day decision analysis in oil and gas management practices. A very attractive and promising technology is the use of time-lapse or 4D seismic as an essential component in subsurface modeling. Today, 4D seismic is enabling oil companies to optimize production and increase recovery through monitoring fluid movements throughout the reservoir. 4D seismic advances are also being driven by an increased need by the petroleum engineering community to become more quantitative and accurate in our ability to monitor reservoir processes. Qualitative interpretations of time-lapse anomalies are being replaced by quantitative inversions of 4D seismic data to produce accurate maps of fluid saturations, pore pressure, temperature, among others. Within all steps involved in this subsurface modeling process, the most demanding one is integrating the geologic model with dynamic field data, including 4Dseismic when available. The validation of the geologic model with observed dynamic data is accomplished through a "history matching" (HM) process typically carried out with well-based measurements. Due to low resolution of production data, the validation process is severely limited in its reservoir areal coverage, compromising the quality of the model and any subsequent predictive exercise. This research will aim to provide a novel history matching approach that can use information from high-resolution seismic data to supplement the areally sparse production data. The proposed approach will utilize streamline-derived sensitivities as means of relating the forward model performance with the prior geologic model. The essential ideas underlying this approach are similar to those used for high-frequency approximations in seismic wave propagation. In both cases, this leads to solutions that are defined along "streamlines" (fluid flow), or "rays" (seismic wave propagation). Synthetic and field data examples will be used extensively to demonstrate the value and contribution of this work. Our results show that the problem of non-uniqueness in this complex history matching problem is greatly reduced when constraints in the form of saturation maps from spatially closely sampled seismic data are included. Further on, our methodology can be used to quickly identify discrepancies between static and dynamic modeling. Reducing this gap will ensure robust and reliable models leading to accurate predictions and ultimately an optimum hydrocarbon extraction.

Download or read book Fast History Matching of Time lapse Seismic and Production data for High Resolution Models written by Alvaro Rey Amaya and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Seismic data have been established as a valuable source of information for the construction of reservoir simulation models, most commonly for determination of the modeled geologic structure, and also for population of static petrophysical properties (e.g. porosity, permeability). More recently, the availability of repeated seismic surveys over the time scale of years (i.e., 4D seismic) has shown promising results for the qualitative determination of changes in fluid phase distributions and pressure required for determination of areas of bypassed oil, swept volumes and pressure maintenance mechanisms. Quantitatively, and currently the state of the art in reservoir model characterization, 4D seismic data have proven distinctively useful for the calibration of geologic spatial variability which ultimately contributes to the improvement of reservoir development and management strategies. Among the limited variety of techniques for the integration of dynamic seismic data into reservoir models, streamline-based techniques have been demonstrated as one of the more efficient approaches as a result of their analytical sensitivity formulations. Although streamline techniques have been used in the past to integrate time-lapse seismic attributes, the applications were limited to the simplified modeling scenarios of two-phase fluid flow and invariant streamline geometry throughout the production schedule. This research builds upon and advances existing approaches to streamline-based seismic data integration for the inclusion of both production and seismic data under varying field conditions. The proposed approach integrates data from reservoirs under active reservoir management and the corresponding simulation models can be constrained using highly detailed or realistic schedules. Fundamentally, a new derivation of seismic sensitivities is proposed that is able to represent a complex reservoir evolution between consecutive seismic surveys. The approach is further extended to manage compositional reservoir simulation with dissolution effects and gravity-convective-driven flows which, in particular, are typical of CO2 transport behavior following injection into deep saline aquifers. As a final component of this research, the benefits of dynamic data integration on the determination of swept and drained volumes by injection and production, respectively, are investigated. Several synthetic and field reservoir modeling scenarios are used for an extensive demonstration of the efficacy and practical feasibility of the proposed developments.

Download or read book Time lapse Seismic Monitoring of Subsurface Fluid Flow written by Sung H. Yuh and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse seismic monitoring repeats 3D seismic imaging over a reservoir to map fluid movements in a reservoir. During hydrocarbon production, the fluid saturation, pressure, and temperature of a reservoir change, thereby altering the acoustic properties of the reservoir. Time-lapse seismic analysis can illuminate these dynamic changes of reservoir properties, and therefore has strong potential for improving reservoir management. However, the response of a reservoir depends on many parameters and can be diffcult to understand and predict. Numerical modeling results integrating streamline fluid flow simulation, rock physics, and ray-Born seismic modeling address some of these problems. Calculations show that the sensitivity of amplitude changes to porosity depend on the type of sediment comprising the reservoir. For consolidated rock, high-porosity models show larger amplitude changes than low porosity models. However, in an unconsolidated formation, there is less consistent correlation between amplitude and porosity. The rapid time-lapse modeling schemes also allow statistical analysis of the uncertainty in seismic response associated with poorly known values of reservoir parameters such as permeability and dry bulk modulus. Results show that for permeability, the maximum uncertainties in time-lapse seismic signals occur at the water front, where saturation is most variable. For the dry bulk-modulus, the uncertainty is greatest near the injection well, where the maximum saturation changes occur. Time-lapse seismic methods can also be applied to monitor CO2 sequestration. Simulations show that since the acoustic properties of CO2 are very different from those of hydrocarbons and water, it is possible to image CO2 saturation using seismic monitoring. Furthermore, amplitude changes after supercritical fluid CO2 injection are larger than liquid CO2 injection. Two seismic surveys over Teal South Field, Eugene Island, Gulf of Mexico, were acquired at different times, and the numerical models provide important insights to understand changes in the reservoir. 4D seismic differences after cross-equalization show that amplitude dimming occurs in the northeast and brightening occurs in the southwest part of the field. Our forward model, which integrates production data, petrophysicals, and seismic wave propagation simulation, shows that the amplitude dimming and brightening can be explained by pore pressure drops and gas invasion, respectively.

Download or read book Reservoir Characterization and History Matching with Uncertainty Quantification Using Ensemble based Data Assimilation with Data Re parameterization written by Mingliang Liu and published by . This book was released on 2021 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir characterization and history matching are essential steps in various subsurface applications, such as petroleum exploration and production and geological carbon sequestration, aiming to estimate the rock and fluid properties of the subsurface from geophysical measurements and borehole data. Mathematically, both tasks can be formulated as inverse problems, which attempt to find optimal earth models that are consistent with the true measurements. The objective of this dissertation is to develop a stochastic inversion method to improve the accuracy of predicted reservoir properties as well as quantification of the associated uncertainty by assimilating both the surface geophysical observations and the production data from borehole using Ensemble Smoother with Multiple Data Assimilation. To avoid the common phenomenon of ensemble collapse in which the model uncertainty would be underestimated, we propose to re-parameterize the high-dimensional geophysics data with data order reduction methods, for example, singular value decomposition and deep convolutional autoencoder, and then perform the models updating efficiently in the low-dimensional data space. We first apply the method to seismic and rock physics inversion for the joint estimation of elastic and petrophysical properties from the pre-stack seismic data. In the production or monitoring stage, we extend the proposed method to seismic history matching for the prediction of porosity and permeability models by integrating both the time-lapse seismic and production data. The proposed method is tested on synthetic examples and successfully applied in petroleum exploration and production and carbon dioxide sequestration.

Download or read book Reservoir Geophysics written by Robert E. Sheriff and published by . This book was released on 1993 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time lapse Seismic Imaging by Linearized Joint Inversion written by Gboyega Olaoye Ayeni and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents methods that overcome some limitations in the application of time-lapse seismic imaging to subsurface reservoir monitoring. These methods attenuate artifacts and distortions in time-lapse seismic images that are caused by differences in survey acquisition geometries, presence of obstructions, complex overburden and man-made noise. Unless these artifacts are attenuated, it is impossible to make reliable deductions about changes in subsurface reservoir properties from time-lapse seismic images. Improvements to two conventional post-imaging seismic cross-equalization methods are considered. Multi-dimensional warping of baseline and monitor images is implemented as sequential one-dimensional cross-correlations and interpolations. This method avoids the cost of full three-dimensional warping, and it avoids errors caused by considering only vertical apparent displacements between images. After warping, matched filters are derived using optimal parameters derived using an Evolutionary Programming algorithm. Applications to four North Sea data sets show that a combination of these two methods provides an efficient and robust cross-equalization scheme. Importantly, the warping method is a key preprocessing tool for linearized joint inversion. Linearized joint inversion of time-lapse data sets is an extension of least-squares migration/inversion of seismic data sets. Linearized inversion improves both structural and amplitude information in seismic images. Joint inversion allows incorporation spatial and temporal regularizations/constraints, which stabilize the inversion and ensure that results are geologically plausible. Implementations of regularized joint inversion in both the data-domain and image-domain are considered. Joint data-domain inversion minimizes a global least-squares objective function, whereas joint image-domain inversion utilizes combinations of target-oriented approximations of the Hessian of the least-squares objective function. Applications to synthetic data sets show that, compared to migration or separate inversion, linearized joint inversion provides time-lapse seismic images that are less sensitive to geometry differences between surveys and to the overburden complexity. An important advantage of an image-domain inversion is that it can be solved efficiently for a small target around the reservoir. Joint image-domain inversion requires careful preprocessing to ensure that the data contain only primary reflections, and that the migrated images are aligned. The importance of various preprocessing steps are demonstrated using two-dimensional time-lapse data subsets from the Norne field. Applications of regularized image-domain joint inversion to the Valhall Life-of-Field Seismic (LoFS) data sets show that it provides improved time-lapse images compared to migration. These applications show that regularized joint image-domain inversion attenuates obstruction artifacts in time-lapse seismic images and that it can be applied to several data sets. Furthermore, because it is computationally efficient, joint image-domain inversion can be repeated quickly using various a priori information.

Download or read book Time Lapse Approach to Monitoring Oil Gas and CO2 Storage by Seismic Methods written by Junzo Kasahara and published by Gulf Professional Publishing. This book was released on 2016-10-14 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time Lapse Approach to Monitoring Oil, Gas, and CO2 Storage by Seismic Methods delivers a new technology to geoscientists, well logging experts, and reservoir engineers, giving them a new basis on which to influence decisions on oil and gas reservoir management. Named ACROSS (Accurately Controlled and Routinely Operated Signal System), this new evaluation method is presented to address more complex reservoirs, such as shale and heavy oil. The book also discusses prolonged production methods for enhanced oil recovery. The monitoring of storage zones for carbon capture are also included, all helping the petroleum and reservoir engineer to fully extend the life of a field and locate untapped pockets of additional oil and gas resources. Rounded out with case studies from locations such as Japan, Saudi Arabia, and Canada, this book will help readers, scientists, and engineers alike to better manage the life of their oil and gas resources and reservoirs. Benefits both geoscientists and reservoir engineers to optimize complex reservoirs such as shale and heavy oil Explains a more accurate and cost efficient reservoir monitoring technology called ACROSS (Accurately Controlled and Routinely Operated Signal System) Illustrates real-world application through multiple case studies from around the world

Download or read book A Data estimation based Approach for Quasi continuous Seismic Reservoir Monitoring written by Adeyemi Temitope Arogunmati and published by Stanford University. This book was released on 2011 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Current strategies and logistics for seismic data acquisition impose restrictions on the calendar-time temporal resolution obtainable for a given time-lapse monitoring program. One factor that restricts the implementation of a quasi-continuous monitoring program using conventional strategies is the time it takes to acquire a complete survey. Here quasi-continuous monitoring describes the process of reservoir monitoring at short time intervals. This dissertation describes an approach that circumvents the restriction by requiring only a subset of a complete survey data each time an image of the reservoir is needed. Ideally, the time interval between survey subset acquisitions should be short so that changes in the reservoir properties are small. The accumulated data acquired are used to estimate the unavailable data at the monitor survey time, and the combined known and estimated data are used to produce an image of the subsurface for monitoring. Quasi-continuous seismic monitoring can be used to monitor geologic reservoirs during the injection phase of a carbon dioxide sequestration project. It can also be used to monitor reservoir changes between injector and producer wells during the secondary recovery phase in an oil field. The primary advantage of a quasi-continuous monitoring strategy over the conventional strategy is the high temporal resolution of the reservoir changes obtainable. Naturally, the spatial resolution of the image obtained using a subset of the data from a full survey will be worse than the spatial resolution of the image obtained using the complete data from a full survey. However, if the unavailable data are estimated perfectly, the spatial resolution is not lost. The choice of estimation algorithm and the size of the known data play an important role in the success of the approach presented in this dissertation.

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

Download or read book Time lapse Seismic Modeling and Production Data Assimilation for Enhanced Oil Recovery and CO2 Sequestration written by Ajitabh Kumar and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Production from a hydrocarbon reservoir is typically supported by water or carbon dioxide (CO2) injection. CO2 injection into hydrocarbon reservoirs is also a promising solution for reducing environmental hazards from the release of green house gases into the earth0́9s atmosphere. Numerical simulators are used for designing and predicting the complex behavior of systems under such scenarios. Two key steps in such studies are forward modeling for performance prediction based on simulation studies using reservoir models and inverse modeling for updating reservoir models using the data collected from field. The viability of time-lapse seismic monitoring using an integrated modeling of fluid flow, including chemical reactions, and seismic response is examined. A comprehensive simulation of the gas injection process accounting for the phase behavior of CO2-reservoir fluids, the associated precipitation/dissolution reactions, and the accompanying changes in porosity and permeability is performed. The simulation results are then used to model the changes in seismic response with time. The general observation is that gas injection decreases bulk density and wave velocity of the host rock system. Another key topic covered in this work is the data assimilation study for hydrocarbon reservoirs using Ensemble Kalman Filter (EnKF). Some critical issues related to EnKF based history matching are explored, primarily for a large field with substantial production history. A novel and efficient approach based on spectral clustering to select 0́optimal0́9 initial ensemble members is proposed. Also, well-specific black-oil or compositional streamline trajectories are used for covariance localization. Approach is applied to the Weyburn field, a large carbonate reservoir in Canada. The approach for optimal member selection is found to be effective in reducing the ensemble size which was critical for this large-scale field application. Streamline-based covariance localization is shown to play a very important role by removing spurious covariances between any well and far-off cell permeabilities. Finally, time-lapse seismic study is done for the Weyburn field. Sensitivity of various bulk seismic parameters viz velocity and impedance is calculated with respect to different simulation parameters. Results show large correlation between porosity and seismic parameters. Bulk seismic parameters are sensitive to net overburden pressure at its low values. Time-lapse changes in pore-pressure lead to changes in bulk parameters like velocity and impedance.

Download or read book Data Integration for the Generation of High Resolution Reservoir Models written by and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this three-year project was to develop a theoretical basis and practical technology for the integration of geologic, production and time-lapse seismic data in a way that makes best use of the information for reservoir description and reservoir performance predictions. The methodology and practical tools for data integration that were developed in this research project have been incorporated into computational algorithms that are feasible for large scale reservoir simulation models. As the integration of production and seismic data require calibrating geological/geostatistical models to these data sets, the main computational tool is an automatic history matching algorithm. The following specific goals were accomplished during this research. (1) We developed algorithms for calibrating the location of the boundaries of geologic facies and the distribution of rock properties so that production and time-lapse seismic data are honored. (2) We developed and implemented specific procedures for conditioning reservoir models to time-lapse seismic data. (3) We developed and implemented algorithms for the characterization of measurement errors which are needed to determine the relative weights of data when conditioning reservoir models to production and time-lapse seismic data by automatic history matching. (4) We developed and implemented algorithms for the adjustment of relative permeability curves during the history matching process. (5) We developed algorithms for production optimization which accounts for geological uncertainty within the context of closed-loop reservoir management. (6) To ensure the research results will lead to practical public tools for independent oil companies, as part of the project we built a graphical user interface for the reservoir simulator and history matching software using Visual Basic.