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1.
Construction of predictive reservoir models invariably involves interpretation and interpolation between limited available data and adoption of imperfect modeling assumptions that introduce significant subjectivity and uncertainty into the modeling process. In particular, uncertainty in the geologic continuity model can significantly degrade the quality of fluid displacement patterns and predictive modeling outcomes. Here, we address a standing challenge in flow model calibration under uncertainty in geologic continuity by developing an adaptive sparse representation formulation for prior model identification (PMI) during model calibration. We develop a flow-data-driven sparsity-promoting inversion to discriminate against distinct prior geologic continuity models (e.g., variograms). Realizations of reservoir properties from each geologic continuity model are used to generate sparse geologic dictionaries that compactly represent models from each respective prior. For inversion initially the same number of elements from each prior dictionary is used to construct a diverse geologic dictionary that reflects a wide range of variability and uncertainty in the prior continuity. The inversion is formulated as a sparse reconstruction problem that inverts the flow data to identify and linearly combine the relevant elements from the large and diverse set of geologic dictionary elements to reconstruct the solution. We develop an adaptive sparse reconstruction algorithm in which, at every iteration, the contribution of each dictionary to the solution is monitored to replace irrelevant (insignificant) elements with more geologically relevant (significant) elements to improve the solution quality. Several numerical examples are used to illustrate the effectiveness of the proposed approach for identification of geologic continuity in practical model calibration problems where the uncertainty in the prior geologic continuity model can lead to biased inversion results and prediction. 相似文献
2.
Tobias Lochbühler Guillaume Pirot Julien Straubhaar Niklas Linde 《Mathematical Geosciences》2014,46(5):625-645
Geophysical tomography captures the spatial distribution of the underlying geophysical property at a relatively high resolution, but the tomographic images tend to be blurred representations of reality and generally fail to reproduce sharp interfaces. Such models may cause significant bias when taken as a basis for predictive flow and transport modeling and are unsuitable for uncertainty assessment. We present a methodology in which tomograms are used to condition multiple-point statistics (MPS) simulations. A large set of geologically reasonable facies realizations and their corresponding synthetically calculated cross-hole radar tomograms are used as a training image. The training image is scanned with a direct sampling algorithm for patterns in the conditioning tomogram, while accounting for the spatially varying resolution of the tomograms. In a post-processing step, only those conditional simulations that predicted the radar traveltimes within the expected data error levels are accepted. The methodology is demonstrated on a two-facies example featuring channels and an aquifer analog of alluvial sedimentary structures with five facies. For both cases, MPS simulations exhibit the sharp interfaces and the geological patterns found in the training image. Compared to unconditioned MPS simulations, the uncertainty in transport predictions is markedly decreased for simulations conditioned to tomograms. As an improvement to other approaches relying on classical smoothness-constrained geophysical tomography, the proposed method allows for: (1) reproduction of sharp interfaces, (2) incorporation of realistic geological constraints and (3) generation of multiple realizations that enables uncertainty assessment. 相似文献
3.
三维地质模型精度评估与误差修正问题已成为制约三维地质模拟技术深入发展应用的瓶颈。在综合国内外研究现状与发展趋势的基础上,提出了三维地质结构模型精度评估、误差检测、动态修正的总体研究框架。在模型精度评估方面,提出分别构建三维地质结构模型精度评估的一般理论模型、面向特定地质体的实际操作模型和地质结构构造不确定性的三维空间分布模型的研究思路,指出应重点研究地质实体自身特性、三维地质建模方法对三维地质结构模型精度的影响,解决由一般地质界面的内插误差和特殊地质体的外推误差引起的精度评估问题。在模型误差修正方面,提出基于建模初始数据的模型误差修正方法和基于建模中间结果的模型误差修正方法,在具体实现时,引入“数据 模型的可视化交互技术”。这些研究成果为建立一套完整的三维地质结构模型精度评估与误差修正的理论体系和方法体系奠定了基础,有助于完善复杂地质条件下三维地质模拟的方法与技术。 相似文献
4.
5.
Aerogeophysical data of an area located on the southern portion of the Guyana shield in Brazil was processed using a fine interpolating mesh, and a corresponding spatial data integration strategy which included the stacking of different high-resolution images, and interpretation following quality control of these. The selected images were correlated to the local known surface geologic units, and to the spatial distribution of the main geochronological provinces of the Amazonian craton. The interpretation of the results also included the available geophysical information for the region, related to Moho depth values, and previously determined SKS shear-wave splitting direction. The observed magnetic regional trends may be strongly influenced by the Proterozoic crustal structure in the area, while radiometric anomalies correlate with the more detailed geologic features. Based on the parallelism among mapped geochronological provinces of the Amazonian craton, and observed geophysical structures on the study area, a geotectonic model is proposed for southern Guyana shield at Proterozoic age. 相似文献
6.
The SISMA prototype system: integrating Geophysical Modeling and Earth Observation for time-dependent seismic hazard assessment 总被引：1，自引：0，他引：1
G. F. Panza A. Peresan A. Magrin F. Vaccari R. Sabadini B. Crippa A. M. Marotta R. Splendore R. Barzaghi A. Borghi L. Cannizzaro A. Amodio S. Zoffoli 《Natural Hazards》2013,69(2):1179-1198
An innovative approach to seismic hazard assessment is illustrated that, based on the available knowledge of the physical properties of the Earth structure and of seismic sources, on geodetic observations, as well as on the geophysical forward modeling, allows for a time-dependent definition of the seismic input. According to the proposed approach, a fully formalized system integrating Earth Observation data and new advanced methods in seismological and geophysical data analysis is currently under development in the framework of the Pilot Project SISMA, funded by the Italian Space Agency. The synergic use of geodetic Earth Observation data (EO) and Geophysical Forward Modeling deformation maps at the national scale complements the space- and time-dependent information provided by real-time monitoring of seismic flow (performed by means of the earthquake prediction algorithms CN and M8S) and permits the identification and routine updating of alerted areas. At the local spatial scale (tens of km) of the seismogenic nodes identified by pattern-recognition analysis, both GNSS (Global Navigation Satellite System) and SAR (Synthetic Aperture Radar) techniques, coupled with expressly developed models for interseismic phase, allow us to retrieve the deformation style and stress evolution within the seismogenic areas. The displacement fields obtained from EO data provide the input for the geophysical modeling, which eventually permits to indicate whether a specific fault is in a “critical state.” The scenarios of expected ground motion (shakemaps) associated with the alerted areas are then defined by means of full waveforms modeling, based on the possibility to compute synthetic seismograms by the modal summation technique (neo-deterministic hazard assessment). In this way, a set of deterministic scenarios of ground motion, which refer to the time interval when a strong event is likely to occur within the alerted area, can be defined both at national and at local scale. The considered integrated approach opens new routes in understanding the dynamics of fault zones as well as in modeling the expected ground motion. The SISMA system, in fact, provides tools for establishing warning criteria based on deterministic and rigorous forward geophysical models and hence allows for a well-controlled real-time prospective testing and validation of the proposed methodology over the Italian territory. The proposed approach complements the traditional probabilistic approach for seismic hazard estimates, since it supplies routinely updated information useful in assigning priorities for timely mitigation actions and hence it is particularly relevant to Civil Defense purposes. 相似文献
7.
Pamela G. Doctor 《Engineering Geology》1989,26(4):411-429
Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high-level radioactive-waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses. 相似文献
8.
Geologic uncertainty in a regulatory environment: An example from the potential Yucca Mountain nuclear waste repository site 总被引：1，自引：0，他引：1
Regulatory geologists are concerned with predicting the performance of sites proposed for waste disposal or for remediation of existing pollution problems. Geologic modeling of these sites requires large-scale expansion of knowledge obtained from very limited sampling. This expansion induces considerable uncertainty into the geologic models of rock properties that are required for modeling the predicted performance of the site.One method for assessing this uncertainty is through nonparametric geostatistical simulation. Simulation can produce a series of equiprobable models of a rock property of interest. Each model honors measured values at sampled locations, and each can be constructed to emulate both the univariate histogram and the spatial covariance structure of the measured data. Computing a performance model for a number of geologic simulations allows evaluation of the effects of geologic uncertainty. A site may be judged acceptable if the number of failures to meet a particular performance criterion produced by these computations is sufficiently low. A site that produces too many failures may be either unacceptable or simply inadequately described.The simulation approach to addressing geologic uncertainty is being applied to the potential high-level nuclear waste repository site at Yucca Mountain, Nevada, U.S.A. Preliminary geologic models of unsaturated permeability have been created that reproduce observed statistical properties reasonably well. A spread of unsaturated groundwater travel times has been computed that reflects the variability of those geologic models. Regions within the simulated models exhibiting the greatest variability among multiple runs are candidates for obtaining the greatest reduction in uncertainty through additional site characterization. 相似文献
9.
Development of technologies for site characterization has grown at a faster pace compared to the development of decision-making methods required for the assimilation of inferences they generate. In the case of geophysical surveying, such dephase adds to the dependency on the use of expert's judgment in the interpretation of geophysical mappings. A systematic assimilation of this type of geo-surveying evidence is required, in particular for the integration of spatial geomorphological information (i.e., stratigraphy), characterized from different geophysical methods. This paper presents a methodology to address this challenge by the use of a probabilistic approach. A set of synthetic geophysical mappings are used to illustrate the applicability of the proposed methodology and its potential extrapolation to other scientific imaging disciplines. 相似文献
10.
Accounting for spatial patterns of multiple geological data sets in geological thematic mapping using GIS-based spatial analysis 总被引：2，自引：0，他引：2
This paper presents a Geographic Information System (GIS)-based spatial analysis scheme to account for spatial patterns and
association in geological thematic mapping with multiple geological data sets. The multi-buffer zone analysis, the main part
of the present study, was addressed to reveal the spatial pattern around geological source primitives and statistical analysis
based on a contingency table was performed to extract information for the assessment of an integrated layer. Mineral potential
mapping using multiple geological data sets from Ogdong in Korea was carried out to illustrate application of this methodology.
The results obtained from the case study indicated that some geochemical elements and residual magnetic anomaly dominantly
affected spatial patterns of the mineral potential map in the study area and the dominant classes of input data layers were
also extracted. This information on spatial patterns of multiple geological data sets around mines could be used as effective
evidences for the interpretation of the integrated layer within GIS. 相似文献
11.
Teacher''s Aide Variogram Interpretation and Modeling 总被引：13，自引：0，他引：13
The variogram is a critical input to geostatistical studies: (1) it is a tool to investigate and quantify the spatial variability of the phenomenon under study, and (2) most geostatistical estimation or simulation algorithms require an analytical variogram model, which they will reproduce with statistical fluctuations. In the construction of numerical models, the variogram reflects some of our understanding of the geometry and continuity of the variable, and can have a very important impact on predictions from such numerical models. The principles of variogram modeling are developed and illustrated with a number of practical examples. A three-dimensional interpretation of the variogram is necessary to fully describe geologic continuity. Directional continuity must be described simultaneously to be consistent with principles of geological deposition and for a legitimate measure of spatial variability for geostatistical modeling algorithms. Interpretation principles are discussed in detail. Variograms are modeled with particular functions for reasons of mathematical consistency. Used correctly, such variogram models account for the experimental data, geological interpretation, and analogue information. The steps in this essential data integration exercise are described in detail through the introduction of a rigorous methodology. 相似文献
12.
The variogram is a critical input to geostatistical studies: (1) it is a tool to investigate and quantify the spatial variability of the phenomenon under study, and (2) most geostatistical estimation or simulation algorithms require an analytical variogram model, which they will reproduce with statistical fluctuations. In the construction of numerical models, the variogram reflects some of our understanding of the geometry and continuity of the variable, and can have a very important impact on predictions from such numerical models. The principles of variogram modeling are developed and illustrated with a number of practical examples. A three-dimensional interpretation of the variogram is necessary to fully describe geologic continuity. Directional continuity must be described simultaneously to be consistent with principles of geological deposition and for a legitimate measure of spatial variability for geostatistical modeling algorithms. Interpretation principles are discussed in detail. Variograms are modeled with particular functions for reasons of mathematical consistency. Used correctly, such variogram models account for the experimental data, geological interpretation, and analogue information. The steps in this essential data integration exercise are described in detail through the introduction of a rigorous methodology. 相似文献
13.
深层重力流水道砂体储层预测方法及效果分析 总被引：2，自引：0，他引：2
由寻找单纯构造圈闭发展到岩性圈闭，及识别隐蔽非背斜岩性圈闭，如何准确对该圈闭进行定量化储层预测描述，以及储层预测的精度、可靠性合理评价，一直是地质研究人员关注的问题。依靠高品质地震、地质、测井、钻井、分析化验等资料，结合地球物理新技术、新方法，围绕深层重力流水道砂体如何从定性分析到定量预测这一核心问题，各种技术方法相互配合，成功地进行了多方法的砂体厚度预测、渗透砂体预测、物性参数预测。经钻井资料验证，均见到较好地质效果，为深层重力流水道砂体发育区的储层定量化预测摸索了一套行之有效的方法。 相似文献
14.
Seismic inverse modeling, which transforms appropriately processed geophysical data into the physical properties of the Earth, is an essential process for reservoir characterization. This paper proposes a work flow based on a Markov chain Monte Carlo method consistent with geology, well-logs, seismic data, and rock-physics information. It uses direct sampling as a multiple-point geostatistical method for generating realizations from the prior distribution, and Metropolis sampling with adaptive spatial resampling to perform an approximate sampling from the posterior distribution, conditioned to the geophysical data. Because it can assess important uncertainties, sampling is a more general approach than just finding the most likely model. However, since rejection sampling requires a large number of evaluations for generating the posterior distribution, it is inefficient and not suitable for reservoir modeling. Metropolis sampling is able to perform an equivalent sampling by forming a Markov chain. The iterative spatial resampling algorithm perturbs realizations of a spatially dependent variable, while preserving its spatial structure by conditioning to subset points. However, in most practical applications, when the subset conditioning points are selected at random, it can get stuck for a very long time in a non-optimal local minimum. In this paper it is demonstrated that adaptive subset sampling improves the efficiency of iterative spatial resampling. Depending on the acceptance/rejection criteria, it is possible to obtain a chain of geostatistical realizations aimed at characterizing the posterior distribution with Metropolis sampling. The validity and applicability of the proposed method are illustrated by results for seismic lithofacies inversion on the Stanford VI synthetic test sets. 相似文献
15.
Rocco Custer Kazuyoshi Nishijima 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2018,12(1):1-13
In natural hazard risk assessment situations are encountered where information on the portfolio of exposure is only available in a spatially aggregated form, hindering a precise risk assessment. Recourse might be found in the spatial disaggregation of the portfolio of exposure to the resolution of the hazard model. Given the uncertainty inherent to any disaggregation, it is argued that the disaggregation should be performed probabilistically. In this paper, a methodology for probabilistic disaggregation of spatially aggregated values is presented. The methodology is exemplified with the disaggregation of a portfolio of buildings in two communes in Switzerland and the results are compared to sample observations. The relevance of probabilistic disaggregation uncertainty in natural hazard risk assessment is illustrated with the example of a simple flood risk assessment. 相似文献
16.
Conditioning complex subsurface flow models on nonlinear data is complicated by the need to preserve the expected geological connectivity patterns to maintain solution plausibility. Generative adversarial networks (GANs) have recently been proposed as a promising approach for low-dimensional representation of complex high-dimensional images. The method has also been adopted for low-rank parameterization of complex geologic models to facilitate uncertainty quantification workflows. A difficulty in adopting these methods for subsurface flow modeling is the complexity associated with nonlinear flow data conditioning. While conditional GAN (CGAN) can condition simulated images on labels, application to subsurface problems requires efficient conditioning workflows for nonlinear data, which is far more complex. We present two approaches for generating flow-conditioned models with complex spatial patterns using GAN. The first method is through conditional GAN, whereby a production response label is used as an auxiliary input during the training stage of GAN. The production label is derived from clustering of the flow responses of the prior model realizations (i.e., training data). The underlying assumption of this approach is that GAN can learn the association between the spatial features corresponding to the production responses within each cluster. An alternative method is to use a subset of samples from the training data that are within a certain distance from the observed flow responses and use them as training data within GAN to generate new model realizations. In this case, GAN is not required to learn the nonlinear relation between production responses and spatial patterns. Instead, it is tasked to learn the patterns in the selected realizations that provide a close match to the observed data. The conditional low-dimensional parameterization for complex geologic models with diverse spatial features (i.e., when multiple geologic scenarios are plausible) performed by GAN allows for exploring the spatial variability in the conditional realizations, which can be critical for decision-making. We present and discuss the important properties of GAN for data conditioning using several examples with increasing complexity.
相似文献17.
矿床模型综合地质信息预测技术研究 总被引：26，自引：2，他引：26
随着中国国民经济持续快速发展,中国对矿产资源的需求呈现了快速增长的趋势,资源短缺已经成为制约中国经济又好又快发展的主要瓶颈之一。为了解决矿产资源短缺问题,对陆地近地表未查明矿产资源潜力的区位、数量和质量的评价工作已经成为当前十分迫切的任务。文章对矿床模型综合地质信息预测技术体系进行了详细、系统的介绍。该体系以地球动力学、成矿动力学和成矿系列理论为指导,深入开展区域地质构造研究,最大限度地分析地质构造的成矿信息,以各级成矿区带为单元,划分主要矿产的矿床预测类型,建立矿床模型,总结区域成矿系列。全面利用物探、化探、遥感等资料所显示的地质找矿信息,运用体现地质成矿规律内涵的预测技术,全面、全过程应用空间数据库及GIS技术,在圈定成矿预测区的基础上估计潜在资源量。 相似文献
18.
本文从辽西－冀北铀矿床成矿地质环境、时空分布及矿床特征出发,以遥感信息为主,综合地质、物化探、水文等资料进行全区联幅分析、复合成图与应用,建立了不同岩区环、弧形构造解译标志并阐述其地质内涵。解译了火山机构、小型封闭沉积盆地和与铀矿密切相关的岩浆岩体,控矿构造和矿化蚀变带的产状、类型,解译了卫片图像“热晕点”并讨论其地质意义及其铀矿的关系,最后建立了遥感地质找矿模式和综合预测模型。 相似文献
19.
Geologic uncertainties and limited well data often render recovery forecasting a difficult undertaking in typical appraisal
and early development settings. Recent advances in geologic modeling algorithms permit automation of the model generation
process via macros and geostatistical tools. This allows rapid construction of multiple alternative geologic realizations.
Despite the advances in geologic modeling, computation of the reservoir dynamic response via full-physics reservoir simulation
remains a computationally expensive task. Therefore, only a few of the many probable realizations are simulated in practice.
Experimental design techniques typically focus on a few discrete geologic realizations as they are inherently more suitable
for continuous engineering parameters and can only crudely approximate the impact of geology. A flow-based pattern recognition
algorithm (FPRA) has been developed for quantifying the forecast uncertainty as an alternative. The proposed algorithm relies
on the rapid characterization of the geologic uncertainty space represented by an ensemble of sufficiently diverse static
model realizations. FPRA characterizes the geologic uncertainty space by calculating connectivity distances, which quantify
how different each individual realization is from all others in terms of recovery response. Fast streamline simulations are
employed in evaluating these distances. By applying pattern recognition techniques to connectivity distances, a few representative
realizations are identified within the model ensemble for full-physics simulation. In turn, the recovery factor probability
distribution is derived from these intelligently selected simulation runs. Here, FPRA is tested on an example case where the
objective is to accurately compute the recovery factor statistics as a function of geologic uncertainty in a channelized turbidite
reservoir. Recovery factor cumulative distribution functions computed by FPRA compare well to the one computed via exhaustive
full-physics simulations. 相似文献
20.
几种电法仪器在地质勘查中的应用 总被引：8，自引：0，他引：8
文章介绍了几类物探电法仪器的工作原理、技术特点和适用范围,强调了物探资料的合理解释必须与地质认识相结合的重要性,物探工作要做实做细,对物探原始资料要选择合理的方法与参量进行计算处理,结合一些具体的勘测实例,说明各种方法的有效性及其实际应用效果. 相似文献