Application of the modified Arps-Roberts discovery proces model to the 1995 U.S. National Oil and Gas Assessment

ARDS (version 4.01), a modified version of the Arps-Roberts discovery process model, was used to forecast the remaining oil and gas resources in more than 50 provinces, super-exploration plays, and individual plays in the onshore and offshore United States for the 1995 National Oil and Gas Assessment. The size distribution of oil and gas fields was estimated for the underlying distribution of fields; the size distribution for the remaining fields was calculated to be the difference between this distribution and that of discovered fields. The guidelines that govern the 1995 National Assessment require the underlying size distribution of fields to be estimated by using only data from two standard commercial data files (the NRG Associates field file and the Petroleum Information Inc. well file). However, a variety of situations required further modification of the discovery process modeling system; for example, multiple exploration plays that occurred nearly simultaneously and also displaced each other in time, and the phenomenon of field growth introduced a large bias in the forecasts produced by the discovery process models for some provinces.     

Discovery process modeling—A sensitivity study

Lognormal discovery process modeling characterizes oil and gas discovery as sampling from a lognormal parent distribution with probability proportional to size and without replacement. In this article, we present a sensitivity study that is based on simulated discovery sequences with different assumptions regarding discovery efficiency, exploration status, and the shape of the parent field size distribution. The results indicate that lognormal discovery process modeling provides good overall estimates of the lognormal parameters if the parent field size distribution is lognormal. If the parent field size distribution is Pareto, an underestimation of the play potential may occur if a lognormal discovery process model is applied. Failure of the likelihood value converging to a maximum is more frequent when sample size is small and/or discovery efficiency is low.     

Discovery Sequence and the Nature of Low Permeability Gas Accumulations

There is an ongoing discussion regarding the geologic nature of accumulations that host gas in low-permeability sandstone environments. This note examines the discovery sequence of the accumulations in low permeability sandstone plays that were classified as continuous-type by the U.S. Geological Survey for the 1995 National Oil and Gas Assessment. It compares the statistical character of historical discovery sequences of accumulations associated with continuous-type sandstone gas plays to those of conventional plays. The seven sandstone plays with sufficient data exhibit declining size with sequence order, on average, and in three of the seven the trend is statistically significant. Simulation experiments show that both a skewed endowment size distribution and a discovery process that mimics sampling proportional to size are necessary to generate a discovery sequence that consistently produces a statistically significant negative size order relationship. The empirical findings suggest that discovery sequence could be used to constrain assessed gas in untested areas. The plays examined represent 134 of the 265 trillion cubic feet of recoverable gas assessed in undeveloped areas of continuous-type gas plays in low permeability sandstone environments reported in the 1995 National Assessment.     

How to Choose Priors for Bayesian Estimation of the Discovery Process Model

The Bayesian version of the discovery process model provides an effective way to estimate the parameters of the superpopulation, the efficiency of the exploration effort, the number of pools and the undiscovered potential in a play. The posterior estimates are greatly influenced by the prior distribution of these parameters. Some empirical and statistical relationships for these parameters can be obtained from Monte Carlo simulations of the discovery model. For example, there is a linear relationship between the expectation of a pool size in logarithms and the order of its discovery, the slope of which is related to the discoverability factor. Some simple estimates for these unknown play parameters can be derived based upon these empirical and statistical conclusions and may serve as priors for the Bayesian approach. The priors and posteriors from this empirical Bayesian approach are compared with the estimates from Lee and Wang's modified maximum likelihood approach using the same data.     

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.     

A comparison of state space and multiple regression for monthly forecasts: U.S. Fuel consumption

Monthly consumption forecasts for U.S. oil, natural gas, and coal are made using state space and multiple regression applied to the same data. These forecasts are compared with actual consumption for a test period. The forecasts made using state space are preferred to those made using multiple regression models for both expost and exante cases. The state space forecasts track data cycles better than do the regression forecasts. Average absolute forecast errors are less for the state space models than they are for the multiple regression models.     

The space-time structure of oil and gas field growth in a complex depositional system

Shortly after the discovery of an oil and gas field, an initial estimate is usually made of the ultimate recovery of the field. With the passage of time, this initial estimate is almost always revised upward. The phenomenon of the growth of the expected ultimate recovery of a field, which is known as field growth, is important to resource assessment analysts for several reasons. First, field growth is the source of a large part of future additions to the inventory of proved reserves of crude oil and natural gas in most petroliferous areas of the world. Second, field growth introduces a large negative bias in the forecast of the future rates of discovery of oil and gas fields made by discovery process models. In this study, the growth in estimated ultimate recovery of oil and gas in fields made up of sandstone reservoirs formed in a complex depositional environment (Frio strand plain exploration play) is examined. The results presented here show how the growth of oil and gas fields is tied directly to the architectural element of the shoreline processes and tectonics that caused the deposition of the individual sand bodies hosting the producible hydrocarbon.     

Oil and gas resource assessment: The linkage between geological analysis and discovery process model results

Two widely-used techniques to estimate the volume of remaining oil and gas resources are discovery process modeling and geologic assessment. Both were used in a recent national assessment of oil and gas resources of the United States. Parallel estimates were obtained for 27 provinces. Geological-based estimates can typically see into areas not available to discovery process models (that is areas with little or no exploration history) and thus, on average, yield higher estimates. However, a linear relation does exist between the mean estimates obtained from these two methods. In addition, other variables were found in a multiple regression model that explained much of the difference. Thus, it is possible to perform discovery process modeling and adjust the estimates to yield results that might be expected from geological-based assessments.     

Israel's petroleum discovery curve

Oil exploration in Israel began in 1953. Until 1991 a total of 263 exploration wells and 122 development wells were drilled, 3 oil fields and 5 gas fields were discovered, and 4 noncommercial oil discoveries and 1 noncommercial gas discovery were made. Proven in-place reserves amount to 70 million barrels of oil equivalent (MMBOE). Exploration focused on six main plays: Syrian Arc anticlines; Mesozoic platform-edge, structural-stratigraphic traps; the Dead Sea graben; Early Mesozoic structures; Saqiye Group biogenic gas; and Hula Group biogenic gas. The more significant discoveries are associated with the first two plays. Ninety percent of the proven reserves were discovered by the first 71 wildcats, which constitute 27 percent of all wildcats drilled to date. During this phase of exploration, the average success was 7 percent, and the average discovery rate was 0.88 MMBOE per wildcat. Most of the following 192 wildcats were dry holes. If, as experts claim, significant reserves are still undiscovered, previous exploration must be deemed inefficient. The quantitative model of the discovery process also leads to such an assessment.     

A petroleum discovery-rate forecast revisited—The problem of field growth

A forecast of the future rates of discovery of crude oil and natural gas for the 123,027-km² Miocene/Pliocene trend in the Gulf of Mexico was made in 1980. This forecast was evaluated in 1988 by comparing two sets of data: (1) the actual versus the forecasted number of fields discovered, and (2) the actual versus the forecasted volumes of crude oil and natural gas discovered with the drilling of 1,820 wildcat wells along the trend between January 1, 1977, and December 31, 1985. The forecast specified that this level of drilling would result in the discovery of 217 fields containing 1.78 billion barrels of oil equivalent; however, 238 fields containing 3.57 billion barrels of oil equivalent were actually discovered. This underestimation is attributed to biases introduced by field growth and, to a lesser degree, the artificially low, pre-1970's price of natural gas that prevented many smaller gas fields from being brought into production at the time of their discovery; most of these fields contained less than 50 billion cubic feet of producible natural gas.     

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 Royalty Revenue Forecast Model for Louisiana

Louisiana receives royalty revenue when minerals are produced on state-owned lands and water bottoms, federal properties within the state, and offshore fields underlying federal and state jurisdiction within 3–6 nautical miles from the coastline. Royalty revenue on oil and gas production has averaged $465 million per year and has contributed 3–7% of the state general revenue over the past decade. The purpose of this article is to develop a royalty revenue forecast model to assist in state budgeting and planning purposes. Producing fields are evaluated within a probabilistic framework to capture the uncertainty associated with future capital outlays and operational changes, and a discovery model is used to generate production from fields expected to be discovered in the future. The forecasts are combined with commodity price scenarios and royalty rate assumptions to generate a royalty revenue outlook for the state. We estimate that cumulative royalty revenue during 2012–2017 will range from $704 million to $1,408 million for oil production and from $286 million to $1,145 million for gas production for commodity prices of 60–120 $/bbl and 2–8 $/Mcf. At $80/bbl and $4/Mcf, cumulative royalty receipts from 2012 to 2017 are estimated at $1,510 million.     

Assessment of oil and gas geopolitical influence

This paper investigated several stages in the formation of the geopolitical influence of oil and gas, including the basis of its gestation, the means of transformation, and the formation and exercise of power. Based on this theoretical framework, a system for assessing the geopolitical influence of oil and gas was developed. This system is comprised of 13 indicators, each with its own method of measurement. Then 21 representative oil and gas importing, exporting, and transit countries were selected as assessment subjects. A quantitative assessment of the geopolitical influence of oil and gas in the selected countries was carried out using the proposed indicators, and factor analysis was used to obtain the main factors of these indicators and the composite score of each country. The empirical results showed that the 13 indicators could be summarized into five main factors, in the order of contribution rate, specifically comprehensive national strength, energy, transportation, risk, and geopolitics, each with its own variance contribution rate. Results of the assessment indicated that the selected countries could be classified into five categories in terms of oil and gas geopolitical influence: strong, relatively strong, moderate, relatively weak, and weak.     

A chain causality model for oil and gas accumulation

The formation of oil and gas reservoirs is the result of infinitesimal amounts of hydrocarbons that accumulate in sedimentary basins through a process of chain reactions, which occur one step at a time. The reactions can be divided into a set of interrelated static factors, which can be divided into a subset of interrelated factors. The chain reactions define a genetic model that has a layered structure with the property of forward chaining. It is an attempt to portray the process of formation of oil and gas reservoirs. By using this model in petroleum exploration, potential pool-size distributions can be evaluated.     

Uncertainty analysis and the relative contributions of geological factors for the Qingshankou source rocks in the North Songliao Basin, northeastern China

Source rock evaluation is a critical factor in resource assessment of oil and gas. Models for evaluating source rocks are dependent on established geomathematical principles, the calculation of source-rock parameters, and geological data. The sensitivities and uncertainties associated with these models are a matter of concern. In this paper, the effects and relative contributions of 13 major geological factors, as well as their variations and distribution probabilities, have been analyzed for the source rocks in the North Songliao Basin in northeastern China. The geological factors include the time of formation of the regional caprock, composition of the regional caprock, the phases of hydrocarbons in migration, and those factors associated with the generation, retention, and expulsion of hydrocarbons and their effects on source-rock efficiency. Of the 13 factors analyzed, the most important are the source-rock depth, sedimentation rate, total organic content, and kerogen-type index; the relative contributions to the uncertainty of efficient gas/oil migration amounts for the most important factors are 37, 25, 19, and 1% for oil and 32, 17, 20, and 15% for gas, respectively. These most reflect the changes that have occurred in the Qingshankou source rocks.     

Exploring the Association of Communication Satisfaction with the Oil and Natural Gas Industry and Risk Perceptions of Shale Energy Development

Despite the vast literature on shale energy development, surprisingly little empirical research has been conducted on the shale energy communicators, communication practices, and community outreach programs. Using data drawn from a random sample of individuals in two counties in the Eagle Ford Shale region of south Texas, we present a newly-constructed unidimensional scale that can be used to measure stakeholders’ level of satisfaction with the oil and natural gas industry’s communication performance. We then examine the relationship between individuals’ level of communication satisfaction with the oil and gas industry and their perceptions of risk in regard to shale energy development in the Eagle Ford Shale. We find substantial support for the hypothesis that communication satisfaction with the oil and natural gas industry is negatively associated with risk perception. We conclude the paper with several suggestions for future research.     

黄土地区输油气管道工程环境风险分析与评价——以陕-甘天然气输气管道工程为例

以陕-甘天然气输气管道工程为例,根据黄土地区特征,经实地考察和有关资料分析,采用类比分析和事故树结构函数计算法,进行了黄土区输气管道工程环境风险因素识别和环境风险定性与定量分析;得出了不同区段环境风险指数和相对排序;提出了黄土区输气管道环境风险的管理措施与对策,为管道安全施工和运营提供了环境保护依据。     

A Simple Way to Model Nonsynchronous Generation of Oil and Gas from Kerogen

Many kinetic models for oil and gas generation use the same kinetics for generation of both oil and gas. In these models, gas is generated at precisely the same time as oil, despite agreement among geochemists that oil generation in nature largely precedes gas generation. Here we present a method for deriving separate kinetics for oil generation and gas generation from the available kinetics for total hydrocarbon generation. The method is based on published data in which oil kinetics are compiled separately from gas kinetics, but it is generalized to be applicable to any of the main kerogen types (I, IIa, IIb, or III), or to any mixtures of those types. Application of this new nonsynchronous model shows that the traditional synchronous models overpredict gas generation by about a factor of two within the oil window, and conversely severely underpredict late gas generation. The nonsynchronous model may predict gas generation several tens of million years later than does the synchronous model. The errors inherent in the synchronous models can be of significance in exploration decisions.     

Distinction Between Oil Expulsion History and Gas Expulsion History

The process of organic matter transformation into oil and gas is also a balance process of hydrocarbon transformation. This article probes to distinguish the oil expulsion history from gas expulsion history based on the hydrocarbon generation, hydrocarbon residual, and hydrocarbon expulsion processes of the source rocks. In this method, the first step is to study the hydrocarbon expulsion rate by means of hydrocarbon generation potential method; the second step is to study the oil generation rate by means of the heating–pressuring experiment method; the third step is to study the oil residual rate by means of the mathematical method. The difference between the values of oil generation rate and oil residual rate is defined as the oil expulsion rate, while that between the values of hydrocarbon expulsion rate and the gas expulsion rate is defined as the gas expulsion rate. Then, combined with the geological parameters of source rocks, the oil and gas expulsion history can be obtained. This study on Es₁ Source rocks, Nanpu Sag, Bohai Bay Basin, China shows that the primary expulsion period of Es₁ source rocks is Guantao–Minghuazhen period.     

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 .