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 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 Dissertation Abstracts International written by and published by . This book was released on 2009 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download or read book Stochastic and Deterministic Inversion Methods for History Matching of Production and Time Lapse Seismic Data written by Shingo Watanabe and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic history matching methods utilize various kinds of inverse modeling techniques. In this dissertation, we examine ensemble Kalman filter as a stochastic approach for assimilating different types of production data and streamline-based inversion methods as a deterministic approach for integrating both production and time-lapse seismic data into high resolution reservoir models. For the ensemble Kalman filter, we develope a physically motivated phase streamline-based covariance localization method to improve data assimilation performance while capturing geologic continuities that affect the flow dynamics and preserving model variability among the ensemble of models. For the streamline-based inversion method, we derived saturation and pressure drop sensitivities with respect to reservoir properties along streamline trajectories and integrated time-lapse seismic derived saturation and pressure changes along with production data using a synthetic model and the Brugge field model. Our results show the importance of accounting for both saturation and pressure changes in the reservoir responses in order to constrain the history matching solutions. Finally we demonstrated the practical feasibility of a proposed structured work- flow for time-lapse seismic and production data integration through the Norne field application. Our proposed method follows a two-step approach: global and local model calibrations. In the global step, we reparameterize the field permeability heterogeneity with a Grid Connectivity-based Transformation with the basis coefficient as parameters and use a Pareto-based multi-objective evolutionary algorithm to integrate field cumulative production and time-lapse seismic derived acoustic impedance change data. The method generates a suite of trade-off solutions while fitting production and seismic data. In the local step, first the time-lapse seismic data is integrated using the streamline-derived sensitivities of acoustic impedance with respect to reservoir permeability incorporating pressure and saturation effects in-between time-lapse seismic surveys. Next, well production data is integrated by using a generalized travel time inversion method to resolve fine-scale permeability variations between well locations. After model calibration, we use the ensemble of history matched models in an optimal rate control strategy to maximize sweep and injection efficiency by equalizing flood front arrival times at all producers while accounting for geologic uncertainty. Our results show incremental improvement of ultimate recovery and NPV values. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/151664

Download or read book Time lapse Seismic Imaging and Uncertainty Quantification written by Maria Kotsi and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-lapse (4D) seismic monitoring is to date the most commonly used technique for estimating changes of a reservoir under production. Full-Waveform Inversion (FWI) is a high resolution technique that delivers Earth models by iteratively trying to match synthetic prestack seismic data with the observed data. Over the past decade the application of FWI on 4D data has been extensively studied, with a variety of strategies being currently available. However, 4D FWI still has challenges unsolved. In addition, the standard outcome of a 4D FWI scheme is a single image, without any measurement of the associated uncertainty. These issues beg the following questions: (1) Can we go beyond the current FWI limitations and deliver more accurate 4D imaging?, and (2) How well do we know what we think we know? In this thesis, I take steps to answer both questions. I first compare the performances of three common 4D FWI approaches in the presence of model uncertainties. These results provide a preliminary understanding of the underlying uncertainty, but also highlight some of the limitations of pixel by pixel uncertainty quantification. I then introduce a hybrid inversion technique that I call Dual-Domain Waveform Inversion (DDWI), whose objective function joins traditional FWI with Image Domain Wavefield Tomography (IDWT). The new objective function combines diving wave information in the data-domain FWI term with reflected wave information in the image-domain IDWT term, resulting in more accurate 4D model reconstructions. Working with 4D data provides an ideal situation for testing and developing new algorithms. Since there are repeated surveys at the same location, not only is the surrounding geology well-known and the results of interest are localized in small regions, but also they allow for better error analysis. Uncertainty quantification is very valuable for building knowledge but is not commonly done due to the computational challenge of exploring the range of all possible models that could fit the data. I exploit the structure of the 4D problem and propose the use of a focused modeling technique for a fast Metropolis-Hastings inversion. The proposed framework calculates time-lapse uncertainty quantification in a targeted way that is computationally feasible. Having the ground truth 4D probability distributions, I propose a local 4D Hamiltonian Monte Carlo (HMC) - a more advanced uncertainty quantification technique - that can handle higher dimensionalities while offering faster convergence.

Download or read book Integration of Time lapse Seismic Data Into Automatic History Matching written by Yannong Dong and published by . This book was released on 2005 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 History Matching Hydromechanical Models Using Time lapse Seismic Time shifts written by David Charles Price and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Assimilation written by Geir Evensen and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.

Download or read book Oilfield Review written by and published by . This book was released on 2004 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 The Rock Physics Handbook written by Gary Mavko and published by Cambridge University Press. This book was released on 2009-04-30 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: A significantly expanded new edition of this practical guide to rock physics and geophysical interpretation for reservoir geophysicists and engineers.

Download or read book Quantitative Seismic Interpretation written by Per Avseth and published by Cambridge University Press. This book was released on 2010-06-10 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Seismic Interpretation demonstrates how rock physics can be applied to predict reservoir parameters, such as lithologies and pore fluids, from seismically derived attributes. The authors provide an integrated methodology and practical tools for quantitative interpretation, uncertainty assessment, and characterization of subsurface reservoirs using well-log and seismic data. They illustrate the advantages of these new methodologies, while providing advice about limitations of the methods and traditional pitfalls. This book is aimed at graduate students, academics and industry professionals working in the areas of petroleum geoscience and exploration seismology. It will also interest environmental geophysicists seeking a quantitative subsurface characterization from shallow seismic data. The book includes problem sets and a case-study, for which seismic and well-log data, and MATLAB® codes are provided on a website (http://www.cambridge.org/9780521151351). These resources will allow readers to gain a hands-on understanding of the methodologies.

Download or read book Geophysics and Geosequestration written by Thomas L. Davis and published by Cambridge University Press. This book was released on 2019-05-09 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the geophysical techniques and analysis methods for monitoring subsurface carbon dioxide storage for researchers and industry practitioners.