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1.
While 3D seismic has been the basis for geological model building for a long time, time-lapse seismic has primarily been used
in a qualitative manner to assist in monitoring reservoir behavior. With the growing acceptance of assisted history matching
methods has come an equally rising interest in incorporating 3D or time-lapse seismic data into the history matching process
in a more quantitative manner. The common approach in recent studies has been to invert the seismic data to elastic or to
dynamic reservoir properties, typically acoustic impedance or saturation changes. Here we consider the use of both 3D and
time-lapse seismic amplitude data based on a forward modeling approach that does not require any inversion in the traditional
sense. Advantages of such an approach may be better estimation and treatment of model and measurement errors, the combination
of two inversion steps into one by removing the explicit inversion to state space variables, and more consistent dependence
on the validity of assumptions underlying the inversion process. In this paper, we introduce this approach with the use of
an assisted history matching method in mind. Two ensemble-based methods, the ensemble Kalman filter and the ensemble randomized
maximum likelihood method, are used to investigate issues arising from the use of seismic amplitude data, and possible solutions
are presented. Experiments with a 3D synthetic reservoir model show that additional information on the distribution of reservoir
fluids, and on rock properties such as porosity and permeability, can be extracted from the seismic data. The role for localization
and iterative methods are discussed in detail. 相似文献
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3.
Investigation of the sampling performance of ensemble-based methods with a simple reservoir model 总被引：1，自引：0，他引：1
The application of the ensemble Kalman filter (EnKF) for history matching petroleum reservoir models has been the subject of intense investigation during the past 10 years. Unfortunately, EnKF often fails to provide reasonable data matches for highly nonlinear problems. This fact motivated the development of several iterative ensemble-based methods in the last few years. However, there exists no study comparing the performance of these methods in the literature, especially in terms of their ability to quantify uncertainty correctly. In this paper, we compare the performance of nine ensemble-based methods in terms of the quality of the data matches, quantification of uncertainty, and computational cost. For this purpose, we use a small but highly nonlinear reservoir model so that we can generate the reference posterior distribution of reservoir properties using a very long chain generated by a Markov chain Monte Carlo sampling algorithm. We also consider one adjoint-based implementation of the randomized maximum likelihood method in the comparisons. 相似文献
4.
Ludwig Zoeller 《Central European Journal of Geosciences》2010,2(1):19-31
This review paper intends to summarize the state of the art in loess research at the first international “Loess-fest’99” conference and to outline progress in loess research during the past decade. The focus is on loess as a terrestrial archive of climatic and environmental change during the Quaternary. The review highlights remarkable new results from regional investigations into European loess, as well as the emergence of new methods and refinements of established techniques, focussing on stratigraphy, dating and palaeoenvironment. It is concluded that loess research during the past decade not only has developed rapidly to take an outstanding place in Quaternary sciences, but also promises exciting perspectives for the next decade, in particular when combined approaches are applied to benefit from the now comprehensive pool of established and new methods. 相似文献
5.
Data assimilation in reservoir modeling often involves model variables that are multimodal, such as porosity and permeability. Well established data assimilation methods such as ensemble Kalman filter and ensemble smoother approaches, are based on Gaussian assumptions that are not applicable to multimodal random variables. The selection ensemble smoother is introduced as an alternative to traditional ensemble methods. In the proposed method, the prior distribution of the model variables, for example the porosity field, is a selection-Gaussian distribution, which allows modeling of the multimodal behavior of the posterior ensemble. The proposed approach is applied for validation on a two-dimensional synthetic channelized reservoir. In the application, an unknown reservoir model of porosity and permeability is estimated from the measured data. Seismic and production data are assumed to be repeatedly measured in time and the reservoir model is updated every time new data are assimilated. The example shows that the selection ensemble Kalman model improves the characterisation of the bimodality of the model parameters compared to the results of the ensemble smoother.
相似文献6.
Using a small ensemble size in the ensemble Kalman filter methodology is efficient for updating numerical reservoir models
but can result in poor updates following spurious correlations between observations and model variables. The most common approach
for reducing the effect of spurious correlations on model updates is multiplication of the estimated covariance by a tapering
function that eliminates all correlations beyond a prespecified distance. Distance-dependent tapering is not always appropriate,
however. In this paper, we describe efficient methods for discriminating between the real and the spurious correlations in
the Kalman gain matrix by using the bootstrap method to assess the confidence level of each element from the Kalman gain matrix.
The new method is tested on a small linear problem, and on a water flooding reservoir history matching problem. For the water
flooding example, a small ensemble size of 30 was used to compute the Kalman gain in both the screened EnKF and standard EnKF
methods. The new method resulted in significantly smaller root mean squared errors of the estimated model parameters and greater
variability in the final updated ensemble. 相似文献
7.
The conventional paradigm for predicting future reservoir performance from existing production data involves the construction of reservoir models that match the historical data through iterative history matching. This is generally an expensive and difficult task and often results in models that do not accurately assess the uncertainty of the forecast. We propose an alternative re-formulation of the problem, in which the role of the reservoir model is reconsidered. Instead of using the model to match the historical production, and then forecasting, the model is used in combination with Monte Carlo sampling to establish a statistical relationship between the historical and forecast variables. The estimated relationship is then used in conjunction with the actual production data to produce a statistical forecast. This allows quantifying posterior uncertainty on the forecast variable without explicit inversion or history matching. The main rationale behind this is that the reservoir model is highly complex and even so, still remains a simplified representation of the actual subsurface. As statistical relationships can generally only be constructed in low dimensions, compression and dimension reduction of the reservoir models themselves would result in further oversimplification. Conversely, production data and forecast variables are time series data, which are simpler and much more applicable for dimension reduction techniques. We present a dimension reduction approach based on functional data analysis (FDA), and mixed principal component analysis (mixed PCA), followed by canonical correlation analysis (CCA) to maximize the linear correlation between the forecast and production variables. Using these transformed variables, it is then possible to apply linear Gaussian regression and estimate the statistical relationship between the forecast and historical variables. This relationship is used in combination with the actual observed historical data to estimate the posterior distribution of the forecast variable. Sampling from this posterior and reconstructing the corresponding forecast time series, allows assessing uncertainty on the forecast. This workflow will be demonstrated on a case based on a Libyan reservoir and compared with traditional history matching. 相似文献
8.
F. Sturt N.C. Flemming D. Carabias H. Jöns J. Adams 《Proceedings of the Geologists' Association. Geologists' Association》2018,129(5):654-683
Submerged prehistory has emerged as a key topic within archaeology over the last decade. During this period the broader academic community has become aware of its potential for revolutionising our understanding of the past. With recent technological and scientific developments has come an opportunity to investigate larger areas and learn more than previously thought possible. When charting the future of the subject, however, it is also necessary to consider its historical trajectory. This sense of opportunity and optimism has been experienced before, but not sustained. As such, our greatest challenge lies not in adopting technological developments, but in maintaining momentum. 相似文献
9.
《地学前缘(英文版)》2016,7(1)
Hydrocarbon production from shale has attracted much attention in the recent years. When applied to this prolific and hydrocarbon rich resource plays, our understanding of the complexities of the flow mechanism(sorption process and flow behavior in complex fracture systems- induced or natural) leaves much to be desired. In this paper, we present and discuss a novel approach to modeling, history matching of hydrocarbon production from a Marcellus shale asset in southwestern Pennsylvania using advanced data mining, pattern recognition and machine learning technologies. In this new approach instead of imposing our understanding of the flow mechanism, the impact of multi-stage hydraulic fractures, and the production process on the reservoir model, we allow the production history, well log, completion and hydraulic fracturing data to guide our model and determine its behavior. The uniqueness of this technology is that it incorporates the so-called "hard data" directly into the reservoir model, so that the model can be used to optimize the hydraulic fracture process. The "hard data" refers to field measurements during the hydraulic fracturing process such as fluid and proppant type and amount, injection pressure and rate as well as proppant concentration. This novel approach contrasts with the current industry focus on the use of "soft data"(non-measured, interpretive data such as frac length, width,height and conductivity) in the reservoir models. The study focuses on a Marcellus shale asset that includes 135 wells with multiple pads, different landing targets, well length and reservoir properties. The full field history matching process was successfully completed using this data driven approach thus capturing the production behavior with acceptable accuracy for individual wells and for the entire asset. 相似文献
10.
Ensemble-based data assimilation methods have recently become popular for solving reservoir history matching problems, but because of the practical limitation on ensemble size, using localization is necessary to reduce the effect of sampling error and to increase the degrees of freedom for incorporating large amounts of data. Local analysis in the ensemble Kalman filter has been used extensively for very large models in numerical weather prediction. It scales well with the model size and the number of data and is easily parallelized. In the petroleum literature, however, iterative ensemble smoothers with localization of the Kalman gain matrix have become the state-of-the-art approach for ensemble-based history matching. By forming the Kalman gain matrix row-by-row, the analysis step can also be parallelized. Localization regularizes updates to model parameters and state variables using information on the distance between the these variables and the observations. The truncation of small singular values in truncated singular value decomposition (TSVD) at the analysis step provides another type of regularization by projecting updates to dominant directions spanned by the simulated data ensemble. Typically, the combined use of localization and TSVD is necessary for problems with large amounts of data. In this paper, we compare the performance of Kalman gain localization to two forms of local analysis for parameter estimation problems with nonlocal data. The effect of TSVD with different localization methods and with the use of iteration is also analyzed. With several examples, we show that good results can be obtained for all localization methods if the localization range is chosen appropriately, but the optimal localization range differs for the various methods. In general, for local analysis with observation taper, the optimal range is somewhat shorter than the optimal range for other localization methods. Although all methods gave equivalent results when used in an iterative ensemble smoother, the local analysis methods generally converged more quickly than Kalman gain localization when the amount of data is large compared to ensemble size. 相似文献
11.
Abiola D. Obembe Sidqi A. Abu-Khamsin M. Enamul Hossain Kassem Mustapha 《Computational Geosciences》2018,22(5):1231-1250
The increasing applications of fractional calculus in simulating the anomalous transport behavior in disordered and fractured heterogeneous porous media has grown rapidly over the past decade. In the present study, a temporal fractional flux relationship is employed as a constitutive equation to relate the volumetric flow rate to the gradient of the pore pressure. The novelty of this paper entails interpreting the time fractional derivative operator in the flux relationship by the Grünwald-Letnikov (G-L) definition as opposed to the Caputo interpretation which has been widely considered. Subsequently, a numerical scheme based on the block-centered finite-difference discretization is formulated to handle the resulting non-linear fractional diffusion model. In addition, a linear stability analysis is successfully performed to establish the stability criterion of the developed numerical scheme. An expression for the modified incremental material balance index was derived to assess the effectiveness of the numerical discretization process. Finally, numerical experiments were performed to provide qualitative insights into the nature of pressure evolution in a hydrocarbon reservoir under the influence subdiffusion. In summary, the results establish that subdiffusion regime results in the development of higher pressure drop in the reservoir. This paper will provide a strong foundation for researchers interested in investigating anomalous diffusion phenomena in porous media. 相似文献
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13.
地下储层构型表征是近十几年发展起来的油气藏开发地质研究方向。与露头构型分析不同的是,地下储层构型表征主要依据地震信息和多井信息,相应地发展了两类方法,其一为地震沉积学(地貌学)方法,即通过三维地震资料地层切片等方式,利用地震成像特征研究沉积单元的分布;其二为多井模式预测方法,即通过将不同级次的定量构型模式与地下井资料(包括动态监测资料)进行拟合,分级约束并预测不同级次的构型单元的井间分布。论述了这两类方法的起源、基本原理、应用范畴及存在问题,并根据油田生产要求与技术发展提出了进一步深入研究的方向,包括三维定量构型模式的深化研究、储层构型地震响应及解释方法研究、多井模拟拟合方法的改进与创新等。 相似文献
14.
Traditional ensemble-based history matching method, such as the ensemble Kalman filter and iterative ensemble filters, usually update reservoir parameter fields using numerical grid-based parameterization. Although a parameter constraint term in the objective function for deriving these methods exists, it is difficult to preserve the geological continuity of the parameter field in the updating process of these methods; this is especially the case in the estimation of statistically anisotropic fields (such as a statistically anisotropic Gaussian field and facies field with elongated facies) with uncertainties about the anisotropy direction. In this work, we propose a Karhunen-Loeve expansion-based global parameterization technique that is combined with the ensemble-based history matching method for inverse modeling of statistically anisotropic fields. By using the Karhunen-Loeve expansion, a Gaussian random field can be parameterized by a group of independent Gaussian random variables. For a facies field, we combine the Karhunen-Loeve expansion and the level set technique to perform the parameterization; that is, for each facies, we use a Gaussian random field and a level set algorithm to parameterize it, and the Gaussian random field is further parameterized by the Karhunen-Loeve expansion. We treat the independent Gaussian random variables in the Karhunen-Loeve expansion as the model parameters. When the anisotropy direction of the statistically anisotropic field is uncertain, we also treat it as a model parameter for updating. After model parameterization, we use the ensemble randomized maximum likelihood filter to perform history matching. Because of the nature of the Karhunen-Loeve expansion, the geostatistical characteristics of the parameter field can be preserved in the updating process. Synthetic cases are set up to test the performance of the proposed method. Numerical results show that the proposed method is suitable for estimating statistically anisotropic fields. 相似文献
15.
M. J. Zandvliet J. F. M. Van Doren O. H. Bosgra J. D. Jansen P. M. J. Van den Hof 《Computational Geosciences》2008,12(4):605-622
Over the past few years, more and more systems and control concepts have been applied in reservoir engineering, such as optimal
control, Kalman filtering, and model reduction. The success of these applications is determined by the controllability, observability,
and identifiability properties of the reservoir at hand. The first contribution of this paper is to analyze and interpret
the controllability and observability of single-phase flow reservoir models and to investigate how these are affected by well
locations, heterogeneity, and fluid properties. The second contribution of this paper is to show how to compute an upper bound
on the number of identifiable parameters when history matching production data and to present a new method to regularize the
history matching problem using a reservoir’s controllability and observability properties. 相似文献
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17.
Justyna K. Przybysz-Jarnut Remus G. Hanea Jan-Dirk Jansen Arnold W. Heemink 《Computational Geosciences》2007,11(1):73-85
A data assimilation method was applied to estimate poorly known parameters (permeabilities) in a numerical reservoir model.
Most variational methods for data assimilation are based on the assumption that the model is perfect except for the poorly
known parameters. The representer method allows also for model errors, i.e. for uncertainties in the state variables (pressures
and saturations). The method is based on minimizing a cost functional, assuming all the errors and parameters to be multivariate
Gaussian random variables with given mean and covariances. The uncertain parameters and variables are expanded into a finite
sum of basis functions called representers, and the gradients of the cost functional are obtained with an adjoint method.
This approach gives an optimal parametrization in the sense that the final result is equal to the solution of the full inverse
problem. The method was tested on a simple one-dimensional model to simulate two-phase (oil-water) flow through a heterogeneous
reservoir. The results show that the method is able to provide an acceptable estimate of the permeability field. We used pressure
measurements from a small number of observation wells in between the injection and production wells, but the representer method
could be used equally well to assimilate data from other sources. The method appears to be a promising data assimilation tool
for applications in reservoir engineering. 相似文献
18.
This review describes developments major and in trace element determination using atomic absorption spectroscopy (AAS), inductively coupled plasma-atomic emission spectrometry (ICP-AES), instrumental neutron activation analysis (INAA), and X-ray fluorescence (XRF) spectrometry that were reported in 2008 and 2009. Publication levels were comparable to those of previous years, except for XRF which showed an increase in the number of articles published in the past 2 years. In terms of number of publications and impact, the most active field was AAS, while INAA was the least active. As expected for well-established and mature methods, novel developments for all four analytical techniques were relatively sparse. For AAS, the most notable publications concerned developments in sample introduction, particularly focussing on solid samples, increasing analyte sensitivity, and higher sample throughput. For ICP-AES, publication of developments in sample introduction, remediation of matrix effects and calibration continues. Compared with past years, there was a clear focus on sample preconcentration methods, but very few publications reporting new hyphenated speciation methods. For INAA, there were several publications exploring the accuracy and robustness of the method, as well as the requirements for INAA to meet criteria for a primary method of measurement. Two other related techniques, delayed neutron activation analysis, and prompt gamma activation analysis, were also described. Hyphenated XRF techniques showed interesting developments in enabling XRF and XRD analysis on the same spot, and further work characterising and calibrating three-dimensional micro-XRF shows promising results for investigating sample heterogeneity. 相似文献
19.
Instability of bank slopes and their failures in reservoirs have become an increasing concern in evaluating potential hazards of hydraulic projects in China as larger hydropower engineering projects have been in operation in the past decade. To provide a quantitative evaluation of such hazards, an evaluation framework has been presented to analyze bank slope stability, identify potential slope failure bed surfaces, and evaluate wave impacts of landslide-induced surges in reservoirs. In this joint analysis framework, reservoir bank slope instability and potential failure surfaces are determined with TFINE model, a nonlinear Finite Element Method (FEM) program using Deformation Reinforcement Theory; the motion of slope failures and resulting surge waves in reservoirs and potential flooding are simulated with COMCOT tsunami simulation package. The work flow and feasibility of this analysis framework are demonstrated through a case study of Guopu slope in Laxiwa reservoir in Southwest China. Three potential failures of Guopu slope are identified through stability analysis and the modeling results of indicate that the potential landslide failures would generate waves with maximum amplitude of 20.9 m in the reservoir, but unlikely causing significant damage to the dam. 相似文献
20.
塔西南前陆冲断带成藏的地质条件具有分段性,即不同构造段成藏条件明显不同。成藏最有利部位是甫沙—克里阳、苏盖特—齐姆根两个构造带,发育了断层传播褶皱及三角带构造,集中了中—下寒武统碳酸盐岩、下石炭统—下二叠统及侏罗系暗色泥岩三套优质烃源岩,拥有下白垩统砂岩储层与古近系膏盐盖层、古近系碳酸盐岩储层与其上覆泥岩盖层、中新统砂岩储层与其中泥岩盖层以及上古生界等一系列优质储盖组合;其次为和田逆冲推覆构造带,准原地系统(原地系统)构造圈闭良好,但烃源条件和储盖条件相对较差,下二叠统克孜里奇曼(P1k)碳酸盐岩烃源岩达到气源岩的标准,下二叠统碳酸盐岩及砂岩储层、下奥陶统碳酸盐岩储层基本上都属低孔低渗型,下二叠统普司格组泥岩属优质区域性盖层;帕米尔前缘冲断带对成藏不太有利,虽有较好的生储盖组合,但发育大型推覆构造及强显露型冲断层,缺乏良好的构造圈闭。 相似文献