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 .     

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.     

Statewide Estimates of Undiscovered Deposits of Gold,Silver, Copper,Lead, and Zinc

Estimates of the number of undiscovered deposits on a statewide basis offer a different perspective on the nation's undiscovered resources of gold, silver, copper, lead, and zinc. Mean estimates of the number of undiscovered deposits statewide were extracted from the estimates of undiscovered deposits nationwide. More than 50 undiscovered deposits are estimated to occur in Alaska, Arizona, Nevada, and Wisconsin. Estimating the number of undiscovered deposits statewide serves as a measure of a state's total remaining mineral resources in known conventional deposit types.     

Probabilistic methodology for estimation of undiscovered petroleum resources in play analysis of the United States

A geostochastic system called FASPF was developed by the U.S. Geological Survey for their 1989 assessment of undiscovered petroleum resources in the United States. FASPF is a fast appraisal system for petroleum play analysis using a field-size geological model and an analytic probabilistic methodology. The geological model is a particular type of probability model whereby the volumes of oil and gas accumulations are modeled as statistical distributions in the form of probability histograms, and the risk structure is bilevel (play and accumulation) in terms of conditional probability. The probabilistic methodology is an analytic method derived from probability theory rather than Monte Carlo simulation. The resource estimates of crude oil and natural gas are calculated and expressed in terms of probability distributions. The probabilistic methodology developed by the author is explained.The analytic system resulted in a probabilistic methodology for play analysis, subplay analysis, economic analysis, and aggregation analysis. Subplay analysis included the estimation of petroleum resources on non-Federal offshore areas. Economic analysis involved the truncation of the field size with a minimum economic cutoff value. Aggregation analysis was needed to aggregate individual play and subplay estimates of oil and gas, respectively, at the provincial, regional, and national levels.     

Estimates of Number of Undiscovered Deposits of Gold,Silver, Copper,Lead, and Zinc in the United States

Estimates of the number of undiscovered deposits offer a unique perspective on the nation's undiscovered mineral resources. As part of the 1998 assessment of undiscovered deposits of gold, silver, copper, lead, and zinc, estimates of the number of deposits were made for 305 of the 447 permissive tracts delineated in 19 assessment regions of the country. By aggregating number of undiscovered deposits by deposit type and by assessment region, a picture of the nation's undiscovered resources has emerged. For the nation as a whole, the mean estimate for the number of undiscovered deposits is 950. There is a 90% chance there are at least 747 undiscovered deposits and a 10% chance there are as many as 1,160 undiscovered deposits. For Alaska, the mean estimate for the number of undiscovered deposits is 281. There is a 90% chance there are at least 168 undiscovered deposits and a 10% chance there are as many as 402 undiscovered deposits. Assuming that the majority of deposits used to create the grade and tonnage models that formed the basis for estimating the number of undiscovered deposits are significant deposits, there remain about as many undiscovered deposits as have already been discovered. Consideration of the number of undiscovered deposits as part of national assessments carried out on a recurring basis serves as a leading indicator of the nation's total mineral 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     

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.

     

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.     

Oil- and gas-resource assessment in certain South American Basins—An application of ARDS (Ver. 5.0) to complex exploration and discovery histories

The modified Arps-Roberts Discovery Process Modeling System [ARDS (Ver. 4.01)] has recently been upgraded [ARDS (Ver. 5.0)] and applied to a wide variety of field discovery and wildcat drilling data with differing characteristics. ARDS is designed to forecast the number and sizes of undiscovered fields in an exploration play or basin by using historical drilling and discovery data. Fields used as input may be grown or ungrown. Two models for field growth—one offshore and the other onshore—have been implemented (Schuenemeyer and Drew, 1996). Uncertainty attributable to field growth is estimated via simulation. This upgrade of ARDS has been designed to handle situations when the data cannot be partitioned into homogeneous regions, but where estimation of the number of remaining oil and gas fields is still meaningful. In this upgrade of ARDS, many restrictions, which include those on the number of fields and wildcat wells required to forecast the size distribution of the oil and gas fields that remain to be discovered in an exploration play, a basin, or other target area, have been removed. In addition, flexibility has been gained by reforming the criteria for convergence of the model. In all, 32 basins and subbasins in South America were examined, 18 of which had sufficient data to be amenable to forecasting the field-size distribution of undiscovered oil and gas resources directly by using the Petroconsultants Inc. (1993) field discovery and wildcat drilling data. Overall, ARDS (Ver. 5.0) performed well in estimating the field-size distribution of undiscovered oil and gas resources in the 18 basins and subbasins. The aggregate volume of undiscovered petroleum resources was characterized by using histograms of the distribution of resources and the following five statistics: the mean, the 80% trimmed mean, and the 10,50 (median), and 90 quantiles. More than 38 billion barrels of oil equivalent (BOE) in fields that contain more than one million BOE individually were forecast as remaining to be discovered. The largest basin, the Campos (Brazil), is forecast to contain nearly 10 billion BOE undiscovered resources. The East Venezuela Basin (excluding the Furrial Trend) is forecast to contain about 8 billion BOE; the Austral-Magallanes Basin (Argentina and Chile), about 7 billion BOE; and the Napo (Colombia and Ecuador) and the Neuquen (Argentina) Basins, between 3 billion and 4 billion BOE. A subset of these basins that illustrate the increased flexibility of ARDS are discussed.     

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.     

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.     

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.     

Recovery Factors of Oil Resources in China

This paper provides a new method to estimate recovery factors of oil resources. The China National Petroleum Assessment (2003–2007) (CNPA 2007) evaluates in-place oil resources and applies the recovery factor (RF) to estimate recoverable oil resources. The RF of oil resources plays an important role in the CNPA 2007. Based on the geological features, 24 types of oil assessment units are defined, such as the Mesozoic rift unit, the Mesozoic and Cenozoic foreland unit, etc. Through the recovery factor statistics of oil reserves (discovered) in different accumulations, as well as the potential analyses of enhanced petroleum recovery, appropriate RF valuing standards of oil resources (discovered and undiscovered) in different assessment units are developed. Calculation methods of oil resource RFs are established, including the appraisal standards, scoring, and calculation steps of oil resource RFs. Through the case studies, the valuing and appraisal standards of oil resource RFs are verified. Robust appraisal standards allow the RF method to be a valuable tool to effective assessment of China’s recoverable oil resources.     

Annotated bibliography of methodology for assessment of undiscovered oil and gas resources

An annotated bibliography of methodology of assessment of undiscovered oil and gas resources is presented as a useful reference for those engaged in resource assessment. The articles that are included deal only with quantitative assessment of undiscovered or inferred resources. the articles in this bibliography are classified largely according to the major assessment method that was applied in each situation. Major assessment methods include areal and volumetric yield methods, field size distributions, historical extrapolation, deposit modeling, organic geochemical mass balance methods, and direct expert assessment. Other categories include mathematical tools, reserve growth/confirmation, quantitative characterization of undiscovered resources, and general topics. For the purpose of future updates, we solicit contributions of articles that may have been missed in the preparation of this bibliography.     

论中国石油立法的缺陷及《石油法》之构想

石油作为对全球的经济、政治、外交、安全起着巨大影响作用的战略物资,影响着当今世界的局势。然而,全球石油资源以及中国石油资源在储量和分布方面的现状是极其严峻的。通过对比研究国外一系列完善的石油法律制度与中国的现行石油法律体制,不难发现目前中国在石油立法方面的许多缺陷。在对进口石油资源依赖程度日益加深的中国,这无疑会对石油资源的稳定供应,战备储备和经济安全上造成严重的威胁。而在此基础之上,逐步建立起以《石油法》为龙头的完善的石油法律体系将具有非常重大的现实意义。     

Assessment of Exploration Bias in Data-Driven Predictive Models and the Estimation of Undiscovered Resources

The spatial distribution of discovered resources may not fully mimic the distribution of all such resources, discovered and undiscovered, because the process of discovery is biased by accessibility factors (e.g., outcrops, roads, and lakes) and by exploration criteria. In data-driven predictive models, the use of training sites (resource occurrences) biased by exploration criteria and accessibility does not necessarily translate to a biased predictive map. However, problems occur when evidence layers correlate with these same exploration factors. These biases then can produce a data-driven model that predicts known occurrences well, but poorly predicts undiscovered resources. Statistical assessment of correlation between evidence layers and map-based exploration factors is difficult because it is difficult to quantify the “degree of exploration.” However, if such a degree-of-exploration map can be produced, the benefits can be enormous. Not only does it become possible to assess this correlation, but it becomes possible to predict undiscovered, instead of discovered, resources. Using geothermal systems in Nevada, USA, as an example, a degree-of-exploration model is created, which then is resolved into purely explored and unexplored equivalents, each occurring within coextensive study areas. A weights-of-evidence (WofE) model is built first without regard to the degree of exploration, and then a revised WofE model is calculated for the “explored fraction” only. Differences in the weights between the two models provide a correlation measure between the evidence and the degree of exploration. The data used to build the geothermal evidence layers are perceived to be independent of degree of exploration. Nevertheless, the evidence layers correlate with exploration because exploration has preferred the same favorable areas identified by the evidence patterns. In this circumstance, however, the weights for the “explored” WofE model minimize this bias. Using these revised weights, posterior probability is extrapolated into unexplored areas to estimate undiscovered deposits.     

Bayesian Discovery Process Modeling of the Lower and Middle Jurassic Play of the Halten Terrace,Offshore Norway,as Compared with the Previous Modeling

A Bayesian version of the discovery process model was applied to the pre-rift Lower and Middle Jurassic play of the Halten Terrace, Mid-Norway. The Bayesian approach estimates the lognormal parameters, the discoverability parameter, and the distribution of sizes of the undiscovered fields as well as the play potential, conditioned on a discovery sequence averaging for all possible prior choices weighted by their likelihood. This approach avoids the problem of having to make arbitrary choices for the parameters. The estimates of parameters and play potential based upon the present methodology compares well with previous estimates, if the play is divided into two sub-plays representing the overpressured and normally pressured zones. These sub-plays have been estimated independently and aggregated in order to get the total undiscovered resource potential. This study estimates that the expected remaining play potential is 100 × 10⁶Sm³ o.e., about 9% of the total resources in the play. There is however a 90% chance that the remaining potential ranges from 13 to 282× 10⁶ Sm³ o.e. and a 5% possibility of exceeding this value.     

北极地区盆地群油气地质特征及其资源潜力

北极地区具有超过4 000亿桶油当量的待发现技术可采储量, 是未来全球油气勘探与开发的重要增长点。本文按照地理和地质构造因素将北极地区分为北冰洋海盆区和环北极含油气区（含潜在含油气盆地）,按照板块演化及盆地发育历史将后者划分为北太平洋极地盆地群、俄罗斯极地盆地群和欧洲极地盆地群。根据大量文献和IHS数据, 结合生油层、储层、盖层及圈闭特征方面的研究, 系统对比、分析北极地区石油、天然气分布特征:北太平洋极地盆地群重要烃源岩形成于侏罗纪和白垩纪, 盆地群中重要储层大部分都分布于新生界布鲁克斯层, 油气系统以构造圈闭为主。俄罗斯极地盆地群中多数盆地具有古生代基底, 受斯堪的纳维亚早古生代造山期变形、西伯利亚板块古生代西部造山变形影响, 60%以上的烃源岩产自中生界, 储层以中生界前陆、克拉通盆地沉积物为主,盖层分布较广, 以中生界居多。欧洲极地盆地群受控于北大西洋洋脊的扩张和迁移, 各盆地烃源岩分布于中生界, 大部分储层分布于上白垩统—古新系, 自生自储、古生新储为该区域盆地的主要成藏模式。其中, 俄罗斯极地盆地油气储量最多, 占北极地区总储量45%以上且勘探潜力最大。     

A National Accounting Framework for the Petroleum Cycle: A Case Study of China

In a world of climate change and socio-economic development, oil is the strategic resource that is closely intertwined and interdependent. Tracing the evolution of petroleum resources flow is fundamental to understanding petroleum supply and demand, and can also serve as the basis for assessing CO₂ emissions from petroleum products. This paper aims to provide a petroleum products flow accounting framework that divides petroleum flow into four phases, three flows, three libraries, and two processes, and summarizes the approach to measure and analyze petroleum resources flows. It takes China as an example for empirical research, and finds that: ① China’s petroleum production, consumption and import have significantly increased over the past two decades, and the combination of increasing demand and limited supply have created an urgent need for China to diversify its petroleum sources globally to ensure its oil security. ② Final consumption accounts for the use of most petroleum products and special attention should be paid to the losses in the petroleum refining process. ③ With the exception of crude oil, petroleum product flows among various sectors has changed greatly. Particularly, the flow of petroleum products into transport and residential consumption has trended upward significantly, whereas the flow to industry is trending downward. ④ CO₂ emission data shows that CO₂ emission amounts increased rapidly from 456Mt in 1993 to 1517Mt in 2013. Previously, the top three CO₂ emitters were the industrial sector, the transport sector including the transport, storage and post segments, and the thermal power sector. Currently, the largest emitters are the transport sector, the industrial sector and the residential consumption sector. Finally, poorly demarcated system boundaries and incomplete databases and models constrain research on industry flows of petroleum resources for non-energy use.     

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.