A probabilistic method for resource appraisal in a petroleum play and its application

A probabilistic method that is based upon conditional probability theory and the laws of expectation has been developed for estimating the undiscovered oil and gas resources in a petroleum play. It takes into account the favorable geological conditions that influence the accumulation of oil and gas and those factors which influence the distribution and the quantity of undiscovered oil and gas. Information about the number and size of undiscovered resources is provided. A practical application in the Turpan-Hami Basin in northwestern China is described. An erratum to this article is available at .     

Geologic risk, economic assessment, and optimal decision making of petroleum plays in the Bohaiwan Basin, northern China

A system of play (trap) assessment based on the analysis of geological characteristics of five different types of petroleum plays in the Bohaiwan Basin, northern China, is proposed. The system makes use of conditional probability, fuzzy logic, and Monte Carlo simulation to assess geologic risk for estimating the undiscovered petroleum resources in a region. Combining the estimates of undiscovered resources with the subsequent economic evaluation of discovered resources by using techniques of optimization, the expected monetary value can be estimated to determine the overall benefits of an investment. A software program has been developed to carry out the calculations.     

Guiding Principles of USGS Methodology for Assessment of Undiscovered Conventional Oil and Gas Resources

During the last 30 years, the methodology for assessment of undiscovered conventional oil and gas resources used by the Geological Survey has undergone considerable change. This evolution has been based on five major principles. First, the U.S. Geological Survey has responsibility for a wide range of U.S. and world assessments and requires a robust methodology suitable for immaturely explored as well as maturely explored areas. Second, the assessments should be based on as comprehensive a set of geological and exploration history data as possible. Third, the perils of methods that solely use statistical methods without geological analysis are recognized. Fourth, the methodology and course of the assessment should be documented as transparently as possible, within the limits imposed by the inevitable use of subjective judgement. Fifth, the multiple uses of the assessments require a continuing effort to provide the documentation in such ways as to increase utility to the many types of users. Undiscovered conventional oil and gas resources are those recoverable volumes in undiscovered, discrete, conventional structural or stratigraphic traps. The USGS 2000 methodology for these resources is based on a framework of assessing numbers and sizes of undiscovered oil and gas accumulations and the associated risks. The input is standardized on a form termed the Seventh Approximation Data Form for Conventional Assessment Units. Volumes of resource are then calculated using a Monte Carlo program named Emc2, but an alternative analytic (non-Monte Carlo) program named ASSESS also can be used. The resource assessment methodology continues to change. Accumulation-size distributions are being examined to determine how sensitive the results are to size-distribution assumptions. The resource assessment output is changing to provide better applicability for economic analysis. The separate methodology for assessing continuous (unconventional) resources also has been evolving. Further studies of the relationship between geologic models of conventional and continuous resources will likely impact the respective resource assessment methodologies.     

A Scenario-Based Hydrocarbon Production Forecast for Louisiana

Conventional oil and gas productions in Louisiana has been in decline for four decades, but in recent years, new technology and capital investment have opened up a significant new resource play in the Haynesville shale, reversing Louisiana’s gas production decline. The need for long-term forecasting has become more important for state planning and for facilitating efficient regulatory development and incentive programs, as the largest oil and gas fields diminish in productivity and the promise of unconventional resources are realized. The purpose of this article is to present a hydrocarbon production forecast for Louisiana using disaggregate resource classes and a transparent analytic framework. A field-level evaluation is employed for producing fields categorized by primary product, resource category, geographic area, and production class. Undiscovered fields are classified according to conventional and unconventional categories and are modeled using a probabilistic and scenario-based forecast. The analytic framework is described along with a discussion of the model results and limitations of the analysis. Louisiana is in the early stages of transitioning to a primarily gas-producing state, and the manner in which the Haynesville shale develops will play a critical role in deliverability and economic prospects in the future.     

Worldwide Estimates of Deep Natural Gas Resources Based on the U.S. Geological Survey World Petroleum Assessment 2000

The U.S. Geological Survey recently assessed undiscovered conventional gas and oil resources in eight regions of the world outside the U.S. The resources assessed were those estimated to have the potential to be added to reserves within the next thirty years. This study is a worldwide analysis of the estimated volumes and distribution of deep (>4.5 km or about 15,000 ft), undiscovered conventional natural gas resources based on this assessment. Two hundred forty-six assessment units in 128 priority geologic provinces, 96 countries, and two jointly held areas were assessed using a probabilistic Total Petroleum System approach. Priority geologic provinces were selected from a ranking of 937 provinces worldwide. The U.S. Geological Survey World Petroleum Assessment Team did not assess undiscovered petroleum resources in the U.S. For this report, mean estimated volumes of deep conventional undiscovered gas resources in the U.S. are taken from estimates of 101 deep plays (out of a total of 550 conventional plays in the U.S.) from the U.S. Geological Survey's 1995 National Assessment of Oil and Gas Resources. A probabilistic method was designed to subdivide gas resources into depth slices using a median-based triangular probability distribution as a model for drilling depth to estimate the percentages of estimated gas resources below various depths. For both the World Petroleum Assessment 2000 and the 1995 National Assessment of Oil and Gas Resources, minimum, median, and maximum depths were assigned to each assessment unit and play; these depths were used in our analysis. Two-hundred seventy-four deep assessment units and plays in 124 petroleum provinces were identified for the U.S. and the world. These assessment units and plays contain a mean undiscovered conventional gas resource of 844 trillion cubic ft (Tcf) occuring at depths below 4.5 km. The deep undiscovered conventional gas resource (844 Tcf) is about 17% of the total world gas resource (4,928 Tcf) based on the provinces assessed and includes a mean estimate of 259 Tcf of U.S. gas from the U.S. 1995 National Assessment. Of the eight regions, the Former Soviet Union (Region 1) contains the largest estimated volume of undiscovered deep gas with a mean resource of343 Tcf.     

Development of an Improved Methodology to Assess Potential Unconventional Gas Resources

Considering the important role played today by unconventional gas resources in North America and their enormous potential for the future around the world, it is vital to both policy makers and industry that the volumes of these resources and the impact of technology on these resources be assessed. To provide for optimal decision making regarding energy policy, research funding, and resource development, it is necessary to reliably quantify the uncertainty in these resource assessments. Since the 1970s, studies to assess potential unconventional gas resources have been conducted by various private and governmental agencies, the most rigorous of which was by the United States Geological Survey (USGS). The USGS employed a cell-based, probabilistic methodology which used analytical equations to calculate distributions of the resources assessed. USGS assessments have generally produced distributions for potential unconventional gas resources that, in our judgment, are unrealistically narrow for what are essentially undiscovered, untested resources. In this article, we present an improved methodology to assess potential unconventional gas resources. Our methodology is a stochastic approach that includes Monte Carlo simulation and correlation between input variables. Application of the improved methodology to the Uinta–Piceance province of Utah and Colorado with USGS data validates the means and standard deviations of resource distributions produced by the USGS methodology, but reveals that these distributions are not right skewed, as expected for a natural resource. Our investigation indicates that the unrealistic shape and width of the gas resource distributions are caused by the use of narrow triangular input parameter distributions. The stochastic methodology proposed here is more versatile and robust than the USGS analytic methodology. Adoption of the methodology, along with a careful examination and revision of input distributions, should allow a more realistic assessment of the uncertainty surrounding potential unconventional gas resources.     

A Framework for Expert Judgment to Assess Oil and Gas Resources

In frontier areas, where well data are sparse, many organizations have used expert judgment to estimate undiscovered resources. In this process, several important issues arise. How should the knowledge be elicited? At what level of aggregation (geologic process model, play, petroleum system, country, etc.) should the assessment be performed? How and at what stage of the assessment process should feedback be given to assessors? Is independent replication of estimates possible? How are issues of dependency treated? When and how should uncertainty be specified? The context for this presentation will be the methodology used in the US Geological Survey's 1998 1002-Arctic National Wildlife Refuge assessment of oil and gas resources.

     

U.S. department of the interior U.S. geological survey: Fractal lognormal percentage analysis of the U.S. geological survey’s 1995 national assessment of conventional oil and gas resources

The U.S. Geological Survey periodically makes appraisals of the oil and gas resources of the Nation. In its 1995 National Assessment the onshore areas and adjoining State waters of the Nation were assessed. As part of the 1995 National Assessment, 274 conventional oil plays and 239 conventional nonassociated-gas plays were assessed. The two datasets of estimates studied herein are the following: (1) the mean, undiscovered, technically recoverable oil resources estimated for each of the 274 conventional oil plays, and (2) the mean, undiscovered, technically recoverable gas resources estimated for each of the 239 conventional nonassociatedgas plays. It was found that the two populations of petroleum estimates are both distributed approximately as lognormal distributions. Fractal lognormal percentage theory is developed and applied to the two populations of petroleum estimates. In both cases the theoretical percentages of total resources using the lognormal distribution are extremely close to the empirical percentages from the oil and nonassociated-gas data. For example, 20% of the 274 oil plays account for 73.05% of the total oil resources of the plays if the lognormal distribution is used, or for 75.52% if the data is used; 20% of the 239 nonassociated-gas plays account for 76.32% of the total nonassociated-gas resources of the plays if the lognormal distribution is used, or for 78.87% if the data is used     

中国海洋油气资源开发与国家石油安全战略对策

石油是中国能源安全的核心问题,随着我国石油供应对外依赖程度的增大,石油安全问题越来越突出,将会成为我国21世纪经济、社会可持续发展面临的一个重要问题。我国是海洋油气资源丰富的国家,广阔的海域中分布着近100×10⁴km²的含油沉积盆地,近海石油资源量为240×10⁸t,天然气资源量为140×10¹²m³。海洋油气资源的开发利用,将能部分解决我国油气资源进口数量。本文讨论了解决石油安全的四种模式,对我国油气安全的国际和国内条件进行了分析,提出了解决我国油气安全的战略对策。     

Uncovering Influences on the Form of Oil and Gas Field Size Distributions

A detailed understanding of the processes that led to empirical oil and gas field size distributions, especially the dynamic character of the discovery process, is needed to improve the quality of forecasts of oil and gas resources. An empirical distribution results from a complex interaction of economic, technical, and social factors with geology in the form of a distribution of deposits. These factors may cause an empirical distribution to mutate nonrandomly through time. Changes in the price of oil, the cost of exploration and development, technology, and access to prospects influence the discovery process. Failure to recognize and account for them in the modeling process can result in serious bias in estimates of the number and volume of future discoveries. In addition, the broad range of some forecasts for a given region may be explained by differences in perspective of those involved in the process. Geologists who understand the basic processes and collect the data may be scientific determinists. Statisticians who model and analyze the data are trained to think in terms of random variables and stochastic processes.     

Correlation between assessments of undiscovered oil and gas resources

There is an inbuilt correlation between estimated quantities of oil and gas produced by probabilistic assessments of undiscovered oil and gas resources. Correlation between assessed quantities of oil and gas occurs at every level, whether prospects, plays, basins, continents, or the world. Providing that the oil and gas are assessed in the same run of the computer program, the correlation can be calculated using the paired values of the undiscovered oil and gas volumes calculated in each of the Monte Carlo simulations. It can be seen in the shape and density of a point plot of these paired values. Alternatively, the correlation can be calculated theoretically using an equation written in terms of the data input to the assessment program. These commonly include distributions for the number of accumulations (N), the success rate (s), the accumulation sizes (V), an oil to gas conversion factor, and a proportion of oil to oil plus gas (P _OOG). The cause of the correlation is investigated and explained using point plots and equations for a variety of input distributions. The shape and density of each plot are determined by the pattern of the numbers of oil and gas accumulations, the sizes of the accumulations, and the proportions of oil to oil plus gas. The correlation is caused by the dispersion or spread of the input distributions. It may be positive or negative, tending toward positive as the dispersions ofN, s, andV increase and the dispersion ofP _OOG decreases. The correlation indicates that there is a relationship between the undiscovered oil and gas resources that may be described by fitting a linear regression to a plot of the paired values of the total oil and gas resources. The relationship should be quoted as part of the assessment and might be used to make a better estimate of the value of the undiscovered resources.     

Quality of the Log-Geometric Distribution Extrapolation for Smaller Undiscovered Oil and Gas Pool Size

The U.S. Geological Survey procedure for the estimation of the general form of the parent distribution requires that the parameters of the log-geometric distribution be calculated and analyzed for the sensitivity of these parameters to different conditions. In this study, we derive the shape factor of a log-geometric distribution from the ratio of frequencies between adjacent bins. The shape factor has a log straight-line relationship with the ratio of frequencies. Additionally, the calculation equations of a ratio of the mean size to the lower size-class boundary are deduced. For a specific log-geometric distribution, we find that the ratio of the mean size to the lower size-class boundary is the same. We apply our analysis to simulations based on oil and gas pool distributions from four petroleum systems of Alberta, Canada and four generated distributions. Each petroleum system in Alberta has a different shape factor. Generally, the shape factors in the four petroleum systems stabilize with the increase of discovered pool numbers. For a log-geometric distribution, the shape factor becomes stable when discovered pool numbers exceed 50 and the shape factor is influenced by the exploration efficiency when the exploration efficiency is less than 1. The simulation results show that calculated shape factors increase with those of the parent distributions, and undiscovered oil and gas resources estimated through the log-geometric distribution extrapolation are smaller than the actual values.     

美国墨西哥湾岸地区石油生产综合体的形成

墨西哥湾岸是美国石油工业的核心地区。本文分析了本地区在有利的区域条件和社会、经济、技术发展要求的共同作用下,石油生产地域综合体的形成过程。分析中强调了主导部门在区域经济开发和区域经济地理研究中的意义。     

基于集对分析的大庆市经济系统脆弱性评价

集对分析是研究客观事物之间确定性与不确定性联系的一种有效的系统理论与方法。将多个评价指标合成一个与最优评价集的相对贴近度,用来评价经济系统的脆弱性程度。基于经济系统脆弱性的内涵,从经济系统对区域可采石油资源逐渐枯竭的敏感性及应对能力两个方面建立了脆弱性评价指标体系,利用熵值法确定各评价指标的权重,运用集对分析法构建经济系统脆弱性评估模型。以典型石油城市大庆为例,分析1991年以来大庆经济系统脆弱性的演变特征及主要影响因素。结果表明:①大庆经济系统对不利扰动的敏感性呈现波动上升趋势,由1991年的0.504增至2007年的0.573;区域应对不利扰动的能力不断增强,由1991年的0.268增至2007年的0.771;经济系统脆弱性整体上呈现不断下降趋势,由初期的0.619降至2007年的0.402。②应对能力的强弱对大庆经济系统脆弱性的影响具有主导作用。③原油产量增长率、人均GDP和工业全员劳动生产率等是影响经济系统脆弱性程度的关键因子。④区域应对能力的"障碍度"分析表明,固定资产投资密度一直是第一障碍因素,而产业结构的限制集中出现在2000年以前。研究认为,大庆经济系统脆弱性呈下降趋势,但仍处于中等脆弱状态,需要重点关注主要敏感因子与障碍因子的发展变化。     

Specification of a Coupled Geological and Wellbore Fluid Dynamics Model for Uncertainty Analysis and Risk-Based Design on a Subsea Oil Project

This paper describes the method and results of a probabilistic risk analysis that was used to provide a quantitative basis for a complex and high-stakes design decision for a subsea oil project. Geologic properties were specified as probability density functions based on information from a small number of exploration and appraisal wells. The geological information was coupled to a wellbore fluid dynamics model to simulate operational outcomes for potential well kill operations. Conventional probabilistic sampling and a more efficient experimental design approach were both employed. The key results are cumulative density functions for critical bases of design that are used for risk analysis and final equipment selection. The analysis reinforces the importance of interdisciplinary collaboration, in this case the subsurface disciplines and well engineering, to achieve efficient risk-based designs.     

Comparison of Methods Used to Estimate Conventional Undiscovered Petroleum Resources: World Examples

Various methods for assessing undiscovered oil, natural gas, and natural gas liquid resources were compared in support of the USGS World Petroleum Assessment 2000. Discovery process, linear fractal, parabolic fractal, engineering estimates, PETRIMES, Delphi, and the USGS 2000 methods were compared. Three comparisons of these methods were made in: (1) the Neuquen Basin province, Argentina (different assessors, same input data); (2) provinces in North Africa, Oman, and Yemen (same assessors, different methods); and (3) the Arabian Peninsula, Arabian (Persian) Gulf, and North Sea (different assessors, different methods). A fourth comparison (same assessors, same assessment methods but different geologic models), between results from structural and stratigraphic assessment units in the North Sea used only the USGS 2000 method, and hence compared the type of assessment unit rather than the method. In comparing methods, differences arise from inherent differences in assumptions regarding: (1) the underlying distribution of the parent field population (all fields, discovered and undiscovered), (2) the population of fields being estimated; that is, the entire parent distribution or the undiscovered resource distribution, (3) inclusion or exclusion of large outlier fields; (4) inclusion or exclusion of field (reserve) growth, (5) deterministic or probabilistic models, (6) data requirements, and (7) scale and time frame of the assessment. Discovery process, Delphi subjective consensus, and the USGS 2000 method yield comparable results because similar procedures are employed. In mature areas such as the Neuquen Basin province in Argentina, the linear and parabolic fractal and engineering methods were conservative compared to the other five methods and relative to new reserve additions there since 1995. The PETRIMES method gave the most optimistic estimates in the Neuquen Basin. In less mature areas, the linear fractal method yielded larger estimates relative to other methods. A geologically based model, such as one using the total petroleum system approach, is preferred in that it combines the elements of petroleum source, reservoir, trap and seal with the tectono-stratigraphic history of basin evolution with petroleum resource potential. Care must be taken to demonstrate that homogeneous populations in terms of geology, geologic risk, exploration, and discovery processes are used in the assessment process. The USGS 2000 method (7th Approximation Model, EMC computational program) is robust; that is, it can be used in both mature and immature areas, and provides comparable results when using different geologic models (e.g. stratigraphic or structural) with differing amounts of subdivisions, assessment units, within the total petroleum system.     

The Geology and Petroleum Resources of Kansas: A Review From Alpha to Omega or From the Pleistocene to the Precambrian

The geological story of Kansas is told through the rocks that are present. It is a simple story in generalities but complex in detail. Knowing the story, gives insight into understanding the occurrence and location of possible economic valuable minerals, such as petroleum. This is a brief review of Kansas geology with respect to the known occurrence of oil and gas. Kansas is part of the Midcontinent oil province with oil having been discovered 150 years ago and commercial production commencing in 1873. Although many prospects remain in Kansas, the state has gone from the number 1 producer in the U.S. in 1916 to 8th today. Exploration for new oil and gas production therefore is going to have to be more imaginative and utilize new approaches and techniques to find the elusive petroleum. There are possibilities however for the prospector who can search diligently. Although the big fields probably have been discovered, the prospects today are deeper, in more undetectable traps, and in essentially untested places.     

The study of the undiscovered mineral resources of the Tongass National Forest and adjacent lands,Southeastern Alaska

The quantitative probabilistic assessment of the undiscovered mineral resources of the 17.1-million-acre Tongass National Forest (the largest in the United States) and its adjacent lands is a nonaggregated, mineral-resource-tract-oriented assessment designed for land-planning purposes. As such, it includes the renewed use of gross-in-place values (GIPV's) in dollars of the estimated amounts of metal contained in the undiscovered resources as a measure for land-use planning.Southeastern Alaska is geologically complex and contains a wide variety of known mineral deposits, some of which have produced important amounts of metals during the past 100 years. Regional geological, economic geological, geochemical, geophysical, and mineral exploration history information for the region was integrated to define 124 tracts likely to contain undiscovered mineral resources. Some tracts were judged to contain more than one type of mineral deposit. Each type of deposit may contain one or more metallic elements of economic interest. For tracts where information was sufficient, the minimum number of as-yet-undiscovered deposits of each type was estimated at probability levels of 0.95, 0.90, 0.50, 0.10, and 0.05.The undiscovered mineral resources of the individual tracts were estimated using the U.S. Geological Survey's MARK3 mineral-resource endowment simulator; those estimates were used to calculate GIPV's for the individual tracts. Those GIPV's were aggregated to estimate the value of the undiscovered mineral resources of southeastern Alaska. The aggregated GIPV of the estimates is $40.9 billion.Analysis of this study indicates that (1) there is only a crude positive correlation between the size of individual tracts and their mean GIPV's: and (2) the number of mineral-deposit types in a tract does not dominate the GIPV's of the tracts, but the inferred presence of synorogenic-synvolcanic nickel-copper, porphyry copper skarn-related, iron skarn, and porphyry copper-molybdenum deposits does. The influence of this study on the U.S. Forest Service planning process is yet to be determined.     

Application of discovery process models in estimating petroleum resources at the play level in China

Discovery process modeling has gained wide acceptance in the Chinese exploration community. In recent years, a variety of discovery process models have been applied to the prediction of undiscovered petroleum resources at the play level in sedimentary basins in China. However, challenging problems have been encountered, particularly when one method alone has been applied to small plays in nonmarine sedimentary basins or in plays with an unusual order of discovery wells. This paper presents results gotten by using the lognormal discovery process model of the Geological Survey of Canada and the geoanchored method for three petroleum plays in basins with different geologic settings. Although the predicted shapes of the parentsize distributions which use these two models, were not always similar, the expected values of the total resources and the number of fields (pools) to be discovered are comparable. The combined use of two discovery process models in the same play compensates for the weaknesses in one method compared with the other and vice versa. Thus, more reliable estimates are the result.     

Quantitative assessment of mineral resources with an application to petroleum geology

The probability of occurrence of natural resources, such as petroleum deposits, can be assessed by a combination of multivariate statistical and geostatistical techniques. The area of study is partitioned into regions that are as homogeneous as possible internally while simultaneously as distinct as possible. Fisher's discriminant criterion is used to select geological variables that best distinguish productive from nonproductive localities, based on a sample of previously drilled exploratory wells. On the basis of these geological variables, each wildcat well is assigned to the production class (dry or producer in the two-class case) for which the Mahalanobis' distance from the observation to the class centroid is a minimum. Universal kriging is used to interpolate values of the Mahalanobis' distances to all locations not yet drilled. The probability that an undrilled locality belongs to the productive class can be found, using the kriging estimation variances to assess the probability of misclassification. Finally, Bayes' relationship can be used to determine the probability that an undrilled location will be a discovery, regardless of the production class in which it is placed. The method is illustrated with a study of oil prospects in the Lansing/Kansas City interval of western Kansas, using geological variables derived from well logs.