Geostatistical Reservoir Characterization Research Articles

A probabilistic assessment of geomechanical reservoir integrity during CO2sequestration in flood basalt formations

AbstractRecent field experiments in Iceland and Washington State (USA) show that basalt formations may be favorable targets for carbon capture and sequestration (CCS) because CO2mineralization reactions proceed rapidly. These results imply that there is tremendous opportunity for implementing CCS in large igneous provinces. However, the magnitude of this opportunity comprises commensurate levels of uncertainty because basalt reservoirs are characterized by highly heterogeneous, fracture‐controlled hydraulic properties. This geologic uncertainty is propagated as parametric uncertainty in quantitative risk models, thus limiting the efficacy of models to predict CCS performance attributes, such as reservoir integrity and storage potential. To overcome these limitations, this study presents a stochastic approach for quantifying the geomechanical performance attributes of CCS operations in a highly heterogeneous basalt reservoir. We utilize geostatistical reservoir characterization to develop an ensemble of equally probable permeability distributions in a flood basalt reservoir with characteristics of the Wallula Basalt Pilot Project. We then simulate industrial‐scale CO2injections within the ensemble and calculate the mean and variance of fluid pressure over a 1‐year injection period. These calculations are combined with the state of stress in southeast Washington State to constrain the spatial extent at which shear failure, fracture initiation, and borehole breakdown may occur. Results from this study show that (i) permeability uncertainty alone causes injection pressure to vary over 25 MPa, (ii) shear failure is likely to occur at 7 times greater distances from the injection than the CO2migrates, and (iii) joint initiation pressures are localized within the volume comprising the CO2plume. © 2019 Society of Chemical Industry and John Wiley & Sons, Ltd.

3D Geostatistical Modeling and Uncertainty Analysis in a Carbonate Reservoir, SW Iran

The aim of geostatistical reservoir characterization is to utilize wide variety of data, in different scales and accuracies, to construct reservoir models which are able to represent geological heterogeneities and also quantifying uncertainties by producing numbers of equiprobable models. Since all geostatistical methods used in estimation of reservoir parameters are inaccurate, modeling of “estimation error” in form of uncertainty analysis is very important. In this paper, the definition of Sequential Gaussian Simulation has been reviewed and construction of stochastic models based on it has been discussed. Subsequently ranking and uncertainty quantification of those stochastically populated equiprobable models and sensitivity study of modeled properties have been presented. Consequently, the application of sensitivity analysis on stochastic models of reservoir horizons, petrophysical properties, and stochastic oil-water contacts, also their effect on reserve, clearly shows any alteration in the reservoir geometry has significant effect on the oil in place. The studied reservoir is located at carbonate sequences of Sarvak Formation, Zagros, Iran; it comprises three layers. The first one which is located beneath the cap rock contains the largest portion of the reserve and other layers just hold little oil. Simulations show that average porosity and water saturation of the reservoir is about 20% and 52%, respectively.

储存库空间的不确定性对在美国爱达荷州东斯内克河平原进行CO2封存的影响

Basalt-hosted hydrogeologic systems have been proposed for geologic CO2 sequestration based on laboratory research suggesting rapid mineralization rates. However, despite this theoretical appeal, little is known about the impacts of basalt fracture heterogeneity on CO2 migration at commercial scales. Evaluating the suitability of basalt reservoirs is complicated by incomplete knowledge of in-situ fracture distributions at depths required for CO2 sequestration. In this work, a numerical experiment is used to investigate the effects of spatial reservoir uncertainty for geologic CO2 sequestration in the east Snake River Plain, Idaho (USA). Two criteria are investigated: (1) formation injectivity and (2) confinement potential. Several theoretical tools are invoked to develop a field-based approach for geostatistical reservoir characterization and their implementation is illustrated. Geologic CO2 sequestration is simulated for 10 years of constant-rate injection at ~680,000 tons per year and modeled by Monte Carlo simulation such that model variability is a function of spatial reservoir heterogeneity. Results suggest that the spatial distribution of heterogeneous permeability structures is a controlling influence on formation injectivity. Analysis of confinement potential is less conclusive; however, in the absence of confining sedimentary interbeds within the basalt pile, rapid mineralization may be necessary to reduce the risk of escape.

堆積物の分布形態解析における統合的手法論序章―堆積学から震探地形学・地球統計学へのリンク―

This paper attempts to seek an effective methodology for integrated sedimentological, seismic geomorphological and geostatistical reservoir-distribution analysis. Recent developments in sedimentology (e.g.,depositional systems and sequence stratigraphy) and 3D seismic geomorphology have improved our understanding of three-dimensional reservoir distributions on the basis of genetic and deterministic concepts. As geologic constraints, the sedimentological and seismic geomorphological information is used for a geostatistical reservoir characterization to obtain realistic distribution maps on reservoir properties. In this characterization flow, it can be efficient that known facts derived from sedimentological concepts are dealt with deterministically, whereas unknown territories (e.g., internal heterogeneity) are dealt with stochastically.

Ranking and Upscaling of Geostatistical Reservoir Models by Use of Streamline Simulation: A Field Case Study

Summary In this paper, we present a field example in which multiple reservoir descriptions were generated to capture uncertainties in reservoir performance; a streamline simulator was used to rank these multimillion-cell geostatistical realizations and to determine the optimum level of vertical upscaling. During geostatistical reservoir characterization, it is a common practice to generate a large number of realizations of the reservoir model to assess the uncertainty in reservoir descriptions and performance predictions. However, only a small fraction of these models can be considered for comprehensive flow simulations because of the high computational costs. A viable alternative is to rank these multiple "plausible" reservoir models on the basis of an appropriate performance criterion that adequately reflects the interaction between heterogeneity and the reservoir flow mechanisms. One can generate thousands of geostatistical realizations with a minimal cost; however, the cost of ranking such realizations can be prohibitively expensive, even if fast streamline simulators are used. The objective is to generate a manageable number of realizations and represent the possible range of uncertainty in reservoir descriptions. Here, we propose a "hierarchical methodology" in designing uncertainties to be represented in reservoir descriptions. In this paper, we also show how a streamline simulator can be used to design vertical upscaling of fine-scale reservoir descriptions. The biggest challenge of upscaling is to reduce model size without losing the heterogeneity level of the original geological model. We use streamline time-of-flight connectivity derived from a streamline simulator. The time of flight reflects fluid-front propagation at various times, and its connectivity at a given time provides us with a direct measure of volumetric sweep efficiency for arbitrary heterogeneity and well configuration. The volumetric sweep efficiency is the simplest measure that reflects the interaction between heterogeneity and the flow field. It is a dynamic measure that can be updated easily to account for changing injection/production conditions. Our field study involves a Middle Eastern carbonate reservoir under a moderate-to-strong aquifer influx. The reservoir is on primary depletion and has no injectors. In our streamline-simulation exercise, the aquifer pressure support is modeled by pseudoinjectors, and pressure updates are used to reflect changing field conditions.

CSEG interviews Olivier Dubrule

Olivier Dubrule graduated as a civil engineer in 1978 from Ecole des Mines de Paris. At that time, the institution's “Centre de Géostatistique” was developing new methods and applications for the petroleum industry and Dubrule was offered the opportunity to work on a PhD with Professor G. Matheron, the father of geostatistics, as his thesis director. Having obtained his PhD in 1981, he was offered a job by Sohio in the United States, where for the next four years he worked on reservoir modeling for the Prudhoe Bay Field. Geostatistics was used mostly through kriging, for mapping petrophysical properties across the field. Next he went to work for Shell International in the Hague. In the mid-1980s geostatistical reservoir characterization was taking off. Object-based models and indicator simulation were subjects of great discussion, but most companies at the time were developing their own software. In 1991 Dubrule moved to Elf to head a reservoir characterization project. One of the results of the project was the first geostatistical inversion software, developed in cooperation with Stanford University. In 1994 Dubrule started a new geologic research group at the Elf Geoscience Research in London, where his team developed geostatistical techniques related to seismic data interpretation, with new tools for structural uncertainty quantification and geostatistical inversion of both seismic and production data. After the merger with Total, Dubrule became head of the Earth Modeling and Uncertainties Group, where they had gathered all the expertise related to uncertainty quantification, earth modeling, and geostatistics. Since 2001 Dubrule has been manager of Geoscience Training and Technical Image at Total. One of his areas of interest is technology transfer; the SEG Distinguished Instructor Short Course, “Geostatistics for Seismic Data Integration in Earth Models,” he taught in 28 cities in 20 countries, is part of this activity.

CSEG interviews Olivier Dubrule

PreviousNext You have accessThe Leading EdgeVolume 22, Issue 9CSEG interviews Olivier Dubrulehttps://doi.org/10.1190/tle22090850.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Olivier Dubrule graduated as a civil engineer in 1978 from Ecole des Mines de Paris. At that time, the institution's “Centre de Géostatistique” was developing new methods and applications for the petroleum industry and Dubrule was offered the opportunity to work on a PhD with Professor G. Matheron, the father of geostatistics, as his thesis director. Having obtained his PhD in 1981, he was offered a job by Sohio in the United States, where for the next four years he worked on reservoir modeling for the Prudhoe Bay Field. Geostatistics was used mostly through kriging, for mapping petrophysical properties across the field. Next he went to work for Shell International in the Hague. In the mid-1980s geostatistical reservoir characterization was taking off. Object-based models and indicator simulation were subjects of great discussion, but most companies at the time were developing their own software. In 1991 Dubrule moved to Elf to head a reservoir characterization project. One of the results of the project was the first geostatistical inversion software, developed in cooperation with Stanford University. In 1994 Dubrule started a new geologic research group at the Elf Geoscience Research in London, where his team developed geostatistical techniques related to seismic data interpretation, with new tools for structural uncertainty quantification and geostatistical inversion of both seismic and production data. After the merger with Total, Dubrule became head of the Earth Modeling and Uncertainties Group, where they had gathered all the expertise related to uncertainty quantification, earth modeling, and geostatistics. Since 2001 Dubrule has been manager of Geoscience Training and Technical Image at Total. One of his areas of interest is technology transfer; the SEG Distinguished Instructor Short Course, “Geostatistics for Seismic Data Integration in Earth Models,” he taught in 28 cities in 20 countries, is part of this activity.FiguresReferencesRelatedDetails Volume 22Issue 9Sep 2003Pages: 801–920ISSN (print):1070-485X ISSN (online):1938-3789 publication data© 2003 © 2003 by The Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 17 Aug 2012Published in print: 01 Sep 2003 CITATION INFORMATION (2003), "CSEG interviews Olivier Dubrule," The Leading Edge 22: 850-854. https://doi.org/10.1190/tle22090850.1 Plain-Language Summary PDF Download Metrics Loading ...

Integrated Characterization and Flow Modeling of a Heterogeneous Carbonate Reservoir in Daleel Field, Oman

Summary This article presents applications of deterministic and conditional geostatistical reservoir characterization methods to the heterogeneous carbonates of the upper Shuaiba formation in Daleel field, Oman. High-resolution reservoir descriptions based on the integration of logs, core, pressure transient tests, geology, and seismic data are constructed; and upscaled for use in reservoir simulation models to history match field performance data. Generally, geostatistical techniques combined with geology and proper upscaling of permeability heterogeneity yield best results without artificial alterations in various fluid and rock properties. Although acceptable history matches can be obtained with compromised less-detailed reservoir descriptions, these require modifications to reservoir data beyond reasonable ranges. Only detailed and concise reservoir descriptions result in history matches that are consistent with a variety of measured data sources.

Downflank hydrocarbon potential identified using seismic inversion and geostatistics: Upper Maastrichtian reservoir unit, Dan Field, Danish Central Graben

Porosities considerably higher than anticipated from porosity/depth trend models are encountered in a Maastrichtian reservoir unit on the western flank of the Dan Field. Because there is a good correlation between seismic impedance and well log porosity, inverted seismic data are used to infer that highly porous zones are widely distributed. The distribution of these high porosity zones is predicted using geostatistical methods based on the inverted seismic data. These predictions contradict the general assumption that porosity deteriorates with depth in the study area. Annealing cosimulation is applied using inversion-derived seismic impedances as soft data and well log porosities as hard data. The sensitivity of the porosity characterization to hydrocarbon in-place estimates is investigated through the calculation of water saturations using height above free water level and simulated porosity as input parameters. Multiple realizations show that calculated hydrocarbon in-place estimates are more sensitive to the location of the free water level than to uncertainties related to the geostatistical reservoir characterization.

Geostatistical reservoir characterization constrained by 3D seismic data

Geostatistical inversion is developed for constraining a 3D geostatistical realization of acoustic impedance using a 3D seismic block. The geostatistical realization is constructed using a sequential variogram-based approach in such a way that the convolutional response of the realization fits with the actual 3D seismic data. The method is illustrated with a 3D synthetic example. The initial acoustic impedance model is generated using an unconditional simulation of one million grid cells. Then, using five wells 'drilled' in this model and the synthetic seismic obtained by convolution, the geostatistical inversion method is applied to reconstruct the initial acoustic impedance model. The 3D synthetic seismic block is matched in a matter of half-an-hour CPU on a standard workstation. Analysis of the results shows that the input geostatistical model (variograms, means and standard deviations) controls the higher and lower frequencies that are not present in the seismic amplitudes. The use of a '3D earth modelling' tool allows efficient management of the '3D earth model' constructed by geostatistical inversion, and visualization of the various inputs and outputs.

The use and abuse of geostatistics

Geostatistical reservoir characterization techniques promise to improve the economics of oil and gas production through the integration of seismic, petrophysical and geologic techniques. Unfortunately, these methods have become veiled with mysterious jargon and the use of geostatistics is too often restricted to a few “experts.” In reality, geostatistical tools are quite simple to use and can be easily mastered. However, these new techniques can only supplement and not replace the correct practice of geophysics, geology, and reservoir engineering.

Can Integrated Reservoir Management And Technology Enhance Performance of Water And Gas Floods?

Abstract This paper outlines critical reservoir management issues and technical areas for effectively managing water and gas floods. A tie between reservoir modelling and performance prediction and decision analysis is illustrated. Case studies are discussed to show the contributions of new and integrated technologies to effective reservoir management. In summary, the companies with a technological leadership position in this area are beginning to harvest the fruits of their actions. Introduction Integrated reservoir management and technology are being increasing applied to maximize economic recovery of oil and gas. The need to enhance recovery from the vast amount of remaining oil- and gas-in-place from existing reservoirs and to maximize recovery from newly discovered fields require the use of integrated technologies and better reservoir management practices(1), Historically, some form of reservoir management has been practiced when a major expenditure is planned, such as a new field development or waterflood installation. The reservoir management practices in these instances most often were not integrated, i.e., different disciplines did their own work separately. During the last five years, however, greater emphasis has been placed on synergism between various functional disciplines, and many companies practicing this are benefiting from their synergistic activities(2). Manyleading-edge technological advances have now been made in geophysics, geology, petrophysics, and reservoir and operations engineering. Mainframe super computers, more powerful personal computers, and workstations are providing ever increasing computing power. Integrated, life-cycle, database-management systems are also being developed and deployed. Integrated, interactive 3D reservoir modelling and simulation assist in describing reservoir geometry and property distribution. In addition, integrated 3D graphics workstations and parallel processors provide the tools to achieve reservoir characterization and modelling efficiently by reviewing the simulation results with other reservoir descriptions and static data and by changing the model, if necessary. Thus, it is now possible for geoscientists and engineers to use new developments in geologic modelling and geostatistical techniques to build a 3D model from static data and edit the model while history matching dynamic data. Combining geostatistical reservoir characterization with high resolution 3D seismic interpretation provides a new dimension in accurately modelling the reservoir. On the other hand, new technologies such as hybrid simulation and scale up provide alternatives to a large-scale computer simulation, yet retaining the geologic heterogeneities in the model. This paper first describes major elements of a successful reservoir management program, and then documents case studies illustrating sound reservoir management and decision analysis practices pertaining to water- and gasflood projects. Elements of Successful Reservoir Management (1) The major elements of a successful reservoir management program are identified below. Data Collection and Management Data collection and management are very important to project success. A clear understanding of the purpose and application of the data is needed, i.e., define why the information is needed and how it is to be used. A cost-benefit analysis of the data, that is, the cost of data collection and management and the benefits to be derived, is mandatory.

Abstract :Advanced Geostatistical Reservoir Characterization

Abstract :Advanced Geostatistical Reservoir Characterization

Adaptation of Reservoir Engineering Software to a DOS/Linux PC

Summary Recent publications have described the implementation of state-of-the-art reservoir engineering applications based on integrated networks of mainframe, workstation, and desktop computers. These facilities provide excellent resources for geologic and engineering applications, but at the cost of substantial investment in computer hardware, network installation, and systems staffing. This paper describes an adaptation of similar state-of-the-art applications to a desktop platform that minimizes the required hardware and system investment. The platform is an Intel 486 or Pentium-based PC with two hard drives and 32 to 64 MB of memory. One disk is partitioned to a standard DOS/Windows environment. The other disk is partitioned to the Linux operating system. Linux is a freely available clone of Unix for the 80386/80486 CPU, which is supported by a worldwide volunteer effort. A machine of this type can be constructed from components for $4,000 to $8,000, depending on CPU and memory. A number of proprietary modeling codes have been ported over so that the PC can provide much of the capability of the network systems. On the Linux disk, there are interactive graphics codes for log analysis, geostatistical reservoir characterization, mapping geologic data into reservoir models, streamtube modeling, and scale up of fine-grid models to coarse grid. On the DOS disk, there are the typical vender-supplied applications for pressure-transient analysis, production analysis, spreadsheet processing, and word processing. A proprietary, general-purpose 3D reservoir simulator is available under both DOS and Linux. The PC can be both networked on the DOS and Linux sides or run stand-alone. If networked, Linux can also provide an X-terminal facility to other Unix or Linux workstations. The PC is sufficiently fast to provide geostatistical processing for reservoirs of several hundred wells. With 64 MB of memory, finite-difference models of up to 20,000 gridblocks can be accommodated for a two-phase, black oil formulation. Using streamtube and hybrid simulation techniques, reservoir models incorporating 300 to 400 wells are practical. We have found the DOS/Linux PC to be useful in several niche situations: remote locations where there is no network, locations where there is insufficient capital budget for a workstation, and locations where network charges are insupportable or the workstations are overloaded.

Improved Reservoir Characterization in Low-Permeability Reservoirs With Geostatistical Models

Summary This paper is a field application of modern geostatistical reservoir characterization to a complex, low-permeability gas reservoir. Multiwell history matching with this approach is shown to be significantly better than those done with historical approaches. Important opportunities for additional drilling were identified; however, these additional infill locations required significantly lower well costs to be commercial.

Impacts of Geostatistical Reservoir Characterization and Modeling Techniques: ABSTRACT

Impacts of Geostatistical Reservoir Characterization and Modeling Techniques: ABSTRACT

Geostatistical Reservoir Characterization of Complex Lateral and Vertical Sequences in a Mixed Carbonate Platform: ABSTRACT

In recent years reservoir characterization through the use of geostatistics has become an almost routine part of production geology. Many techniques are available within the broad title of geostatistics, having been developed in response to many types of problem. One characteristic feature of almost all techniques (Stochastic Indicator Simulation, Boolean [open quotes]object[close quotes] Modeling, Gaussian [and Truncated Gaussian] methods and Optimized Markov-fields) is their reliance on the concept of quantifiable correlations, which reflect some aspect of the shape of [open quotes]objects.[close quotes] For example, almost any of the above noted techniques, and their variants, could be used to model fluvial, deltaic, or turbiditic reservoirs because in each case facies can be described in terms of geometries (channels, lobes, etc.). This study considers the complex lateral and vertical variations of a mixed carbonate platform environment, where facies cannot be easily characterized by simple geometries. The complex heterogeneities are a function of changes in sea level, representing fluctuations over several orders of cyclicity. Given facies have no characteristic form, being the product of the interplay between sediment supply and sea level change. This type of environment is, therefore, characterized by a good deal of information concerning trends in the data, while correlationsmore » and geometries are almost meaningless. Associated with the concepts of cyclicity, rules concerning the reappearance of facies, or otherwise, were developed. For example, minor recurrences of maximum flooding surfaces could be tolerated within individual units but other specified recurrences need to be excluded.« less