共查询到20条相似文献，搜索用时 531 毫秒
1.
The objective of a field development optimization process, or workflow, is to investigate various options and determine a course of action that will deliver the largest expected value from an asset. The analysis is often complicated by uncertainty in important inputs. Ideally, operators desire workflows and tools that integrate reservoir engineering and optimization principles in a fast-solving model that can be used to explore the full range of the uncertain inputs. This need is acute in the screening and concept selection stage where the primary objective is to determine the sensitivity of competing concepts to the sources of uncertainty. In these early stages, model results can be used to determine whether additional information should be collected, and to narrow down the number of competing options. The objective of this research is the development of a workflow and tool that integrates reservoir response surfaces within a project optimization model that contains facility and operational options, and to use this model to investigate the impacts of uncertainty on decision making. The integration of technical options is critical because a static view of capital investment and facility constraints causes a systematic undervaluation and can introduce error to development decisions. The new workflow and integrated reservoir-economic optimization tool developed in this research leverage methods and engineering work products that are already known to industry, for example, experimental design (ED) and response surface methods (RSMs). A demonstration is provided for a gas flood project using a stylized reservoir. Specifically, we investigate the selection of initial well configurations and injection capacities while simultaneously accounting for the options to update these decisions after production information is acquired in the early periods of production. The workflow is used to optimize the development of a gas flood. As a second step, the workflow is used to solve a value of information problem. 相似文献
2.
Shale-Gas Assessment: Comparison of Gas-In-Place Versus Performance-Based Approaches 总被引：1，自引：0，他引：1
H. Stueck D. Houseknecht D. Franke D. Gautier A. Bahr S. Ladage 《Natural Resources Research》2016,25(3):315-329
The recent interest in exploration for shale gas increases the demand for a reliable, compatible resource assessment. Many different assessment methods are used, commonly depending on types and quantity of data available, which may lead to significantly divergent results for the same shale-gas play. This study compares results obtained using performance-based and gas-in-place methodologies to assess a well-developed and active shale-gas play (Woodford Shale, Arkoma Basin, USA) and two untested, hypothetical shale-gas plays (Shublik and Brookian, Alaska North Slope, USA). Results show that the two assessment methods produce comparable results when assessment units are identically defined and similar geological constraints are used as input parameters. Inherent uncertainties are associated with both assessment methods, and these are related to aspects of shale-gas production that are not well understood. The performance-based method relies on decline trend analysis to generate distributions of estimated ultimate recovery (EUR), and uncertainty increases in cases of short production history. The gas-in-place method requires the application of a recovery factor to estimate technically recoverable resources, and both absolute values of recovery factors and their spatial variability are poorly documented, and therefore a source of uncertainty. 相似文献
3.
Jean-Jacques Schott Michel Roussignol Michel Menvielle & Flavien R. Nomenjahanary 《Geophysical Journal International》1999,138(3):769-783
In this paper, we will report on the application of Bayesian inference to DC resistivity inversion for 1-D multilayer models. The posterior probability distribution is explored through a Markov process based upon a Gibbs's sampler. The process would lead to unrealistic estimates without additional prior information, which takes the form of a second Markov chain where the transition kernel corresponds to a smoothness constraint. The outcomes are posterior marginal probabilites for each parameter, as well as, if required, joint probabilities for pairs of parameters. We will discuss the main properties of the method in the light of a theoretical example and illustrate its capabilities with some field examples taken from various contexts. 相似文献
4.
Based upon the Bayesian framework for analyzing the discovery sequence in a play, a Markov chain Monte Carlo sampler—the Metropolis–Hastings algorithm, is employed to sample model parameters and pool sizes from their joint posterior distribution. The proposed sampling scheme ensures that the parameter space of changing dimension can be traversed in spite of the unknown number of pools. The equal sample weights make it easy to obtain the confidence intervals and assess the statistical error in the estimates, so that the statistical behaviors of the discovery process modeling can be well understood. Two application examples of the Halten play in Norwegian Sea and the Bashaw reef play in the Western Canada Basin show that, the computational advantage of this method to the simple Monte Carlo integration is considerable. In order to increase the convergence speed of the sample chains to the posterior distributions, several parallel simulations with different starting values are recommended. 相似文献
5.
Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)-simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al2O3) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard.
相似文献6.
Tian Yapeng Ju Binshan Wang Xudong Wang Hongya Hu Jie Huang Yingsong Liu Nannan Dong Yintao 《Natural Resources Research》2021,30(5):3533-3549
The phase behavior of fluid is essential for predicting ultimate oil recovery and determining optimal production parameters. The pore size in shale porous media is nanopore, which causes different phase behaviors of fluid in unconventional reservoirs. Nanopores in shale media can be regard as semipermeable membrane to filter heavy components (sieving effect) in shale oil, which leads to the different distributions of fluid components and different phase behaviors. In addition, the phase behavior of fluid in nanopores can be significantly altered by large capillary pressure. In this paper, the phase behavior of fluid in shale reservoirs is investigated by a new two-phase flash algorithm considering sieving effect and capillary pressure. Firstly, membrane efficiency and capillary pressure are introduced to establish a thermodynamic equilibrium model that is solved by Rachford–Rice flash calculation and Newton–Raphson method. The capillary pressures in different pore sizes are calculated by the Young–Laplace equation. Then, the influences of sieving effect and capillary pressure on phase behavior are analyzed. The results indicate that capillary pressure can suppress the bubble point pressure of fluid in nanopores. The distributions of fluid components are different in various parts of shale media. In the unfiltered part, density and viscosity of fluid are higher. Finally, it is found that the membrane efficiency can be improved by CO2 injection. The minimum miscibility pressure for shale oil–CO2 system is also studied. The developed model provides a better understanding of the phase behavior of fluid in shale oil reservoirs.
相似文献7.
A fundamental geologic problem in the Steam-Assisted Gravity Drainage (SAGD) heavy oil developments in the McMurray Formation
of Northern Alberta is to determine the location of shales in the reservoirs that may interfere with the steaming or recovery
process. Petrophysical analysis shows that a key acoustic indicator of the presence of shale is bulk density. In theory, density
can be derived from seismic data using Amplitude Versus Offset (AVO) analysis of conventional or multicomponent seismic data,
but this is not widely accepted in practice. However, with billions of dollars slated for SAGD developments in the upcoming
years, this technology warrants further investigation. In addition, many attributes can be investigated using modern tools
like neural networks; so, the density extracted from seismic using AVO can be compared and combined with more conventional
attributes in solving this problem. Density AVO attributes are extracted and correlated with “density synthetics” created
from the logs just as the seismic stack correlates to conventional synthetics. However, multiattribute tests show that more
than density is required to best predict the volume proportion of shale (Vsh). Vsh estimates are generated by passing seismic
attributes derived from conventional PP, and multicomponent PS seismic, AVO and inversion from an arbitrary line following
the pilot SAGD wells through a neural network. This estimate shows good correlation to shale proportions estimated from core.
The results have encouraged the application of the method to the entire 3D. 相似文献
8.
Seda Şalap-Ayça Piotr Jankowski Keith C Clarke Phaedon C Kyriakidis Atsushi Nara 《International journal of geographical information science》2018,32(4):637-662
The paper presents a computationally efficient meta-modeling approach to spatially explicit uncertainty and sensitivity analysis in a cellular automata (CA) urban growth and land-use simulation model. The uncertainty and sensitivity of the model parameters are approximated using a meta-modeling method called polynomial chaos expansion (PCE). The parameter uncertainty and sensitivity measures obtained with PCE are compared with traditional Monte Carlo simulation results. The meta-modeling approach was found to reduce the number of model simulations necessary to arrive at stable sensitivity estimates. The quality of the results is comparable to the full-order modeling approach, which is computationally costly. The study shows that the meta-modeling approach can significantly reduce the computational effort of carrying out spatially explicit uncertainty and sensitivity analysis in the application of spatio-temporal models. 相似文献
9.
K. David Newell 《Natural Resources Research》2007,16(1):55-66
Drill cuttings can be used for desorption analyses but with more uncertainty than desorption analyses done with cores. Drill
cuttings are not recommended to take the place of core, but in some circumstances, desorption work with cuttings can provide
a timely and economic supplement to that of cores. The mixed lithologic nature of drill cuttings is primarily the source of
uncertainty in their analysis for gas content, for it is unclear how to apportion the gas generated from both the coal and
the dark-colored shale that is mixed in usually with the coal. In the Western Interior Basin Coal Basin in eastern Kansas
(Pennsylvanian-age coals), dark-colored shales with normal (∼100 API units) gamma-ray levels seem to give off minimal amounts
of gas on the order of less than five standard cubic feet per ton (scf/ton). In some cuttings analyses this rule of thumb
for gas content of the shale is adequate for inferring the gas content of coals, but shales with high-gamma-ray values (>150
API units) may yield several times this amount of gas. The uncertainty in desorption analysis of drill cuttings can be depicted
graphically on a diagram identified as a “lithologic component sensitivity analysis diagram.” Comparison of cuttings desorption
results from nearby wells on this diagram, can sometimes yield an unique solution for the gas content of both a dark shale
and coal mixed in a cuttings sample. A mathematical solution, based on equating the dry, ash-free gas-contents of the admixed
coal and dark-colored shale, also yields results that are correlative to data from nearby cores. 相似文献
10.
Calvin A. Whealton Jery R. Stedinger Jared D. Smith Teresa E. Jordan Franklin G. Horowitz Maria C. Richards 《International journal of geographical information science》2020,34(10):2053-2076
ABSTRACT The focus of this work is general methods for prioritization or screening of project sites based on the favorability of multiple spatial criteria. We present a threshold-based transformation of each underlying spatial favorability factor into a continuous scale with a common favorability interpretation across all criteria. We compare several methods of computing site favorability and propagating uncertainty from the data to the favorability metrics. Including uncertainty allows decision makers to determine if seeming differences among sites are significant. We address uncertainty using Taylor series approximations and analytical distributions, which are compared to computationally intensive Monte Carlo simulations. Our methods are applied to siting direct-use geothermal energy projects in the Appalachian Basin, where our knowledge about any particular site is limited, yet sufficient data exist to estimate favorability. We consider four factors that contribute to site favorability: the thermal resource described by the depth to 80°C rock, natural reservoir productivity described by rock permeability and thickness, potential for induced seismicity, and the estimated cost of surface infrastructure for heat distribution. Those factors are combined in three ways. We develop favorability uncertainty propagation and sensitivity analysis methods. All methods are general and can be applied to other multi-criteria spatial screening problems. 相似文献
11.
An important aim of modern geostatistical modeling is to quantify uncertainty in geological systems. Geostatistical modeling
requires many input parameters. The input univariate distribution or histogram is perhaps the most important. A new method
for assessing uncertainty in the histogram, particularly uncertainty in the mean, is presented. This method, referred to as
the conditional finite-domain (CFD) approach, accounts for the size of the domain and the local conditioning data. It is a
stochastic approach based on a multivariate Gaussian distribution. The CFD approach is shown to be convergent, design independent,
and parameterization invariant. The performance of the CFD approach is illustrated in a case study focusing on the impact
of the number of data and the range of correlation on the limiting uncertainty in the parameters. The spatial bootstrap method
and CFD approach are compared. As the number of data increases, uncertainty in the sample mean decreases in both the spatial
bootstrap and the CFD. Contrary to spatial bootstrap, uncertainty in the sample mean in the CFD approach decreases as the
range of correlation increases. This is a direct result of the conditioning data being more correlated to unsampled locations
in the finite domain. The sensitivity of the limiting uncertainty relative to the variogram and the variable limits are also
discussed. 相似文献
12.
Minimum Acceptance Criteria for Geostatistical Realizations 总被引：2，自引：0，他引：2
Geostatistical simulation is being used increasingly for numerical modeling of natural phenomena. The development of simulation as an alternative to kriging is the result of improved characterization of heterogeneity and a model of joint uncertainty. The popularity of simulation has increased in both mining and petroleum industries. Simulation is widely available in commercial software. Many of these software packages, however, do not necessarily provide the tools for careful checking of the geostatistical realizations prior to their use in decision-making. Moreover, practitioners may not understand all that should be checked. There are some basic checks that should be performed on all geostatistical models. This paper identifies (1) the minimum criteria that should be met by all geostatistical simulation models, and (2) the checks required to verify that these minimum criteria are satisfied. All realizations should honor the input information including the geological interpretation, the data values at their locations, the data distribution, and the correlation structure, within acceptable statistical fluctuations. Moreover, the uncertainty measured by the differences between simulated realizations should be a reasonable measure of uncertainty. A number of different applications are shown to illustrate the various checks. These checks should be an integral part of any simulation modeling work flow. 相似文献
13.
Weishan Ren Jason A. Mclennan Oy Leuangthong Clayton V. Deutsch 《Natural Resources Research》2006,15(2):111-117
There is a need to estimate reserve uncertainty for large lease areas. Detailed 3D models of heterogeneity are not necessarily
required, but there is a need to integrate all available data into an in-situ reserve estimate with uncertainty. A 2D mapping
approach is presented to appraise reserves accounting for multiple variables, multiple data sources, and uncertainty. The
approach can be considered in three primary steps: (1) Bayesian updating is used to determine local distributions of uncertainty
for each primary variable while integrating multiple secondary information, (2) matrix simulation is employed to jointly and
simultaneously simulate multiple collocated variables to determine a derived variable such as OOIP, and (3) probability field
simulation then is applied to permit joint simulation of multiple locations. This methodology permits local and global uncertainty
assessment while integrating multiple sources of information. An application to the McMurray Formation in Alberta, Canada
is demonstrated. 相似文献
14.
水文模型是认识水文科学规律、分析水文过程及研究水文循环机理的重要科学工具。水文模型模拟结果的不确定分析是提高模型可靠性、进行有效水情预报的一个重要研究内容。参数不确定性是影响水文模型模拟结果不确定性的关键因素之一,开展模型参数不确定性及其影响因素分析对水文预报具有重要现实意义。目前的参数不确定性分析方法大致可分为3类：参数敏感性分析、参数优化以及考虑无资料流域参数值估计的参数区域化方法。论文归纳总结了近年来国内外水文模型参数不确定性分析工作的主要研究进展,分析了不同方法的优点与不足,提出了未来水文模型不确定性分析方法研究的潜在发展方向。借助多学科理论和技术方法,加强水文模型不确定性分析系统性方法的研究,是水文学科当前的迫切需求及发展趋势。 相似文献
15.
Monica Wachowicz Tianyu Liu 《International journal of geographical information science》2016,30(9):1806-1831
ABSTRACTCurrently the increase in the variety and volume of data sources is demanding new data analytical workflows for exploring them concurrently, especially if the goal is to detect spatial outliers. In this paper, we propose a data analytical workflow for exploring Call Detail Records in conjunction with geotagged tweets. The aim was to investigate how massive data point observations can be analyzed to detect spatial outliers in collective mobility patterns that are coupled with social ties. This workflow consists of analytical tasks that are developed based on the a-priori assumption of two isometric spaces where Natural Language Processing techniques are used to find spatial clusters from geotagged tweets in a Social Space which are later used to aggregate the Call Detail Records generated by antennas located in the Mobility Space. The dynamic weighted centroids that are given by the mean location of the number of calls per hour of all antennas that belong to a particular cluster are used to compute Standard Deviation Ellipses. The longer the period of time a weighted centroid stays outside of the 99.7% probability region of an ellipse, the highest the likelihood that they are spatial outliers. The workflow was implemented for the city of Dakar in Senegal. The results indicate that the further the hourly weighted centroids are skewed from the normal mean of an ellipse, the stronger the influence of a cluster is in finding spatial outliers. Furthermore, the longer the period of time the outliers stays outside of the 99.7% probability region of an ellipse, the highest the likelihood that the outliers are genuine and can be associated to extraordinary events such as natural disasters and national holidays. 相似文献
16.
Hannes Römer Jens Kersten Ralph Kiefl Stefan Plattner Alexander Mager Stefan Voigt 《International journal of geographical information science》2014,28(4):682-699
A critical requirement for an effective and coordinated response by public entities tasked with management, security, and relief during large-scale public events or natural disasters is the availability of current situational information. However, today there is a lack of comprehensive operational systems allowing a near-real-time (NRT) collection, visualization, and provision of situational information for larger areas. In this study a methodological framework is proposed, which allows an NRT extraction and visualization of situational information based on aerial image acquisition. The framework combines digital image analysis using a generic supervised information extraction approach based on statistical modeling with a downstream web-based visualization component realized through an automatic update of web services. Even though being applicable for different scenarios, the workflow will be demonstrated for the specific use-case of a NRT monitoring of open spaces including assembly and parking areas. Compared to other approaches, image analysis results indicate a high robustness and a low demand for computational power sources (7 seconds per image). Due to a high degree of automation, the proposed workflow contributes to a NRT ‘end-to-end’ monitoring system, which was developed within the VABENE (German acronym for ‘traffic management under large-scale public events and disaster conditions’) project covering all parts from the acquisition of raw aerial imagery to the dissemination of information products to end-users. 相似文献
17.
Guocheng Pan 《Natural Resources Research》1996,5(1):53-76
The weights of evidence modeling (WEM) for binary patterns is extended to take account of general categorical variables. The extension makes it possible to use the weights of evidence model in estimating the conditional probability distributions of metal grades. First, the target feature is converted into a set of binary target indicators. Second, the posterior probabilities are estimated for each of the target categories. Third, the estimates are combined to yield the posterior probability distribution of the target feature. Finally, the pseudometal estimates are derived from the probability distribution. The metal grade estimates are prefixed with pseudo, because the estimates are created from indirect evidence (explanatory variables). The pseudo-estimates provide a unique quantitative means to the delineation of exploration targets. This advantage reduces the ambiguities of target selection based solely on probability estimates. In order to use the generalized WEM, continuous geoscience attributes must be converted into categorical variables by means of optimal segmentation based on the target attribute of interest. The segmentation may be viewed as a process of defining evidence of the target feature. The extended weights of evidence model is demonstrated on a case study to select gold targets of Carlin type. The dataset used in the modeling includes apparent resistivity fields, soil geochemical samples, lithological and alteration information, and structural data. 相似文献
18.
This paper describes a hybrid fuzzy weights-of-evidence (WofE) model for mineral potential mapping that generates fuzzy predictor
patterns based on (a) knowledge-based fuzzy membership values and (b) data-based conditional probabilities. The fuzzy membership
values are calculated using a knowledge-driven logistic membership function, which provides a framework for treating systemic
uncertainty and also facilitates the use of multiclass predictor maps in the modeling procedure. The fuzzy predictor patterns
are combined using Bayes’ rule in a log-linear form (under an assumption of conditional independence) to update the prior
probability of target deposit-type occurrence in every unique combination of predictor patterns. The hybrid fuzzy WofE model
is applied to a regional-scale mapping of base-metal deposit potential in the south-central part of the Aravalli metallogenic
province (western India). The output map of fuzzy posterior probabilities of base-metal deposit occurrence is classified subsequently
to delineate zones with high-favorability, moderate favorability, and low-favorability for occurrence of base-metal deposits.
An analysis of the favorability map indicates (a) significant improvement of probability of base-metal deposit occurrence
in the high-favorability and moderate-favorability zones and (b) significant deterioration of probability of base-metal deposit
occurrence in the low-favorability zones. The results demonstrate usefulness of the hybrid fuzzy WofE model in representation
and in integration of evidential features to map relative potential for mineral deposit occurrence. 相似文献
19.
The Alberta Deep Basin in western Canada has undergone a large amount of erosion following deep burial in the Eocene. Basin modeling and simulation of burial and temperature history require estimates of maximum overburden for each gridpoint in the basin model. Erosion can be estimated using shale compaction trends. For instance, the widely used Magara method attempts to establish a sonic log gradient for shales and uses the extrapolation to a theoretical uncompacted shale value as a first indication of overcompaction and estimation of the amount of erosion. Because such gradients are difficult to establish in many wells, an extension of this method was devised to help map erosion over a large area. Sonic t values of one suitable shale formation are calibrated with maximum depth of burial estimates from sonic log extrapolation for several wells. This resulting regression equation then can be used to estimate andmap maximum depth of burial or amount of erosion for all wells in which this formation has been logged. The example from the Alberta Deep Basin shows that the magnitude of erosion calculated by this method is conservative and comparable to independent estimates using vitrinite reflectance gradient methods. 相似文献
20.
Li Jing Li Pengpeng Zhou Shixin Meng Bingkun Sun Zexiang Zhang Xiaodong 《Natural Resources Research》2021,30(6):4843-4859
Natural Resources Research - Nanoporosity is a key factor for evaluating shale oil/gas potential and recovery. Organic matter (OM) can be a primary host of nanopores in shale. The Triassic Yanchang... 相似文献