Estimates Of Gas Reserves Research Articles

Estimation of CO2 storage capacities in saline aquifers using material balance

Estimating CO2 storage capacities is crucial in developing carbon capture and storage projects. Material balance equation (MBE) methods, widely employed for oil and gas reserve estimation, offer a direct approach to estimating CO2 storage capacities. However, previous MBE methods rely on an original fluid in-place volume calculated using volumetric methods to estimate CO2 storage capacities, lacking validation for accuracy. It is essential to accurately estimate the original fluid in-place volume, representing the pore volume, as it substantially influences CO2 storage capacity. This study presents a refined MBE method that ensures accurate estimates of CO2 storage capacities by validating the original fluid in-place volumes in saline aquifers. The accuracy of this method was evaluated by comparing it with a commercial reservoir simulator for a synthetic aquifer example and the Sleipner L9 model. In the synthetic aquifer example, the relative error in CO2 storage capacity estimation with the proposed MBE method was only 2.09%, even when short-term (1-year) injection data were utilized. The proposed MBE method demonstrates consistent accuracy in estimating CO2 storage capacities under different aquifer properties, operating conditions, and MBE-related conditions. The proposed MBE method also accurately estimated the CO2 storage capacity in the Sleipner L9 model, achieving a relative error of 3.47%.

Log-exponential transformation function for interpreting NMR relaxation measurements of hydrocarbon in organic porous media for enhancing absolute adsorption estimation

Assessing unconventional petroleum resources, particularly shale gas reserve estimation, is challenging due to the adsorption phenomenon. This study presents a new method combining experimental and mathematical procedures to determine the absolute adsorption amount in shale samples. In the experimental section of this study, a new behavior was observed in the NMR decay time series of hydrocarbons in organic porous media. The fast section has a linear relationship with time rather than an exponential one. As a result, a Log-Exponential fit to these decay curves was proposed. Then the logarithmic portion was then used to estimate the absolute adsorbed amount. The method was validated against literature data and conventional methods.Based on this newly developed method, absolute adsorption isotherms were obtained for a Duvernay shale sample and activated carbon packs at pressures ranging from 0.77 MPa to 7 MPa. The model proved to be applicable and consistent with pressure variations. Methane in Duvernay shale exhibited adsorbed isotherm type V, with a methane adsorption capacity of 0.08 g per gram of Total Organic Content (TOC) at 6.24 MPa.In addition to absolute adsorption, the competitive adsorption of methane and CO2 was explored, which is critical for evaluating CO2-enhanced shale gas recovery and storage techniques. The injected CO2 resulted in the displacement of methane from smaller shale pores to larger ones.Adsorption and desorption experiments were conducted to investigate hysteresis. The new method was able to better describe the physical behavior of gaseous hydrocarbons in organic porous media. It was able to capture phase transition and critical pressure specific to organic porous media, which differ from non-organic porous media. This innovative approach enables the accurate characterization of shale reservoirs.

Reliable Technologies Combine To Establish Reasonable Certainty for Reserves Estimates

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 210358, “Establishing Reasonable Certainty for Reserves Estimates by Using a Combination of Reliable Technologies,” by Keshav Narayanan, SPE, Peter Gale, SPE, and J.P. Blangy, SPE, Woodside Energy, et al. The paper has not been peer reviewed. The Petroleum Resources Management System (PRMS) and many regulatory agencies require what is termed “reasonable certainty” for Proved Reserves estimates. The guidance provided by the PRMS or the US Securities and Exchange Commission (SEC) for establishing reasonable certainty is general in nature because of the difficulty in explicitly describing all possible scenarios and also allows leeway to use new technologies in the future. The complete paper addresses the complex challenge of establishing reasonable certainty in reserves and resource assessments and discusses how multiple reliable technologies may be used in concert to establish reasonable certainty for reserves estimates through the flexibility provided by the PRMS. Introduction The authors write that a common response to many questions seeking clarification on reserves-related matters is that “it depends.” Likewise, regarding the question of what constitutes reliable technology, the answer depends on the specific circumstances and the data being considered. The use of reliable technology as a method to improve certainty in the estimates of oil and gas reserves was formally recognized in the 2008 modernization of oil and gas reporting. The PRMS issued in 2007 and further updated in 2018 also recognized the use of appropriate technologies that can lead to more-reliable estimates of reserves. However, the SEC or the PRMS guidelines also seem to recognize that it might not be possible to prescribe a definitive approach that could work for any set of circumstances. They broadly describe the framework for what constitutes reliable technology and how it can be used to establish reasonable certainty. Operators have an obligation to use a scientific method to build a robust case to justify categorization of volumes. Previous Research Previous work reviewed how the industry, in the years from 2008 to 2016, had been using reliable technologies for reserves estimates and how industry practitioners were demonstrating and describing that these applications were consistent with the SEC and PRMS guidelines. The material surveyed by previous researchers can be grouped into the following broad themes: - Seismic applications, which establish water contacts downdip of well controls and explore how seismic amplitude processes can be relied on to improve probability of geologic success - Dynamic simulations, which investigate when reasonable certainty can be demonstrated when simulation models are used - Unconventional applications, which include how reasonable certainty should be established when booking proved, undeveloped reserves (PUD) away from well control - SEC comment letters, which can require registrant companies to more-clearly spell out the demonstration of reasonable certainty - Applications of multiple reliable technologies increase confidence in free-water level determined by use of pressure data or seismic amplitude shutoffs, seal-capacity analysis, well logs, pressure data, and seismic to support proved reserves estimates

Integrating Petrophysical Analysis and Seismic Interpretation for Oil and Gas Reserves Estimation in “TAU” Field, Jatibarang Sub–Basin, North West Java Basin

The focus of the study is the North West Java Basin, specifically the Jatibarang Sub Basin within it. The research aims to identify new potential areas for hydrocarbon reserves using seismic interpretation, and tetrophysical analysis, also calculate the volume of reserves in those areas. According to the study, 2 potential areas for hydrocarbon reserves were identified in the Parigi Formation, 2 were identified in the Baturaja Formation, 3 were identified in the Talang Akar Formation, and 1 was identified in the Jatibarang Formation. No new potential areas were discovered in the Cibulakan Formation. The study used petrophysical interpretation of six wells to determine the average values of shale volume (9.57% to 29.87%), effective porosity (19.45% to 21.67%), and water saturation (69.73% to 93.50%) for each potential zone. The TAU-5 well in the Baturaja Formation (Zone 1, Zone 2, Zone 3, and Zone 4) was determined to be the most economically viable zone for production based on the values of shale volume, porosity, and water saturation. The volume of hydrocarbon reserves in the BR-1 potential zone was calculated to be 182.741281 MBO in OOIP and 177.85122 BCF in OGIP. The BR-2 potential zone had an OOIP value of 1,197.534148 MBO and an OGIP of 1165.488764 BCF.

Adoption of machine learning in estimating compressibility factor for natural gas mixtures under high temperature and pressure applications

One of the essential properties of natural gas is its compressibility factor (z-factor), which is required for the efficient design of natural gas pipelines, storage facilities, gas well testing, gas reserve estimation, etc. Its importance has led to the development of several approaches involving new laboratory methods, equations of state (EOS), empirical correlations, and artificial intelligence for estimating gas compressibility factors. Most of the developed Z factor models have a limited range of applicability. They are unsuitable for predicting Z factors of highly pressurized gas reservoirs and natural gas systems with pseudo-reduced temperatures less than 1. Where such models exist, they are scarce and less accurate. In this study, three machine learning models, including the Gradient Boosted Decision Tree (GBDT), Support Vector Regression (SVR), and Radial Basis Function-Neural Network (RBF-NN), were developed for predicting the z-factor of natural gas mixtures with a range of Ppr and Tpr of 0–30 and 0.92–3.0, respectively. The results showed that the Gradient Boosted Decision Tree (GBDT) model outperformed other selected machine learning algorithms and published correlations. The proposed model gave a superior coefficient of determination (R2 score), and root mean square (RMSE) of 0.99962 and 0.01033, respectively. Also, the variation of the Z factors from the GBDT model with pseudo-reduced pressures at different pseudo-reduced temperatures using the isotherm plot was found to be adequate. Hence, the GBDT model in this study is a reliable method for predicting Z factors of natural gas mixtures with Ppr and Tpr of 0–30 and 0.92–3.0, respectively. The plot revealed that the GBDT model performed extremely well in predicting compressibility factor with an MAPE of about 1%. The findings of this study shows that the proposed intelligent model can be utilized in predicting the gas Z-factor.

Research Methods of Main Parameter Sensitivity Differences in China’s Dynamic Oil and Gas Reserve Estimation under SEC Standards

International oil and gas companies listed in New York must publish the information of oil and gas reserves under the SEC (United States Securities and Exchange Commission) standards every year. For greatly improving the SEC reserve, the SEC reserve value and the SEC reserve substitution rate, in this article not only the SEC reserve equations have been determined but also the SEC reserve value models have been established. The SEC reserve value models have been verified as correct. Based on these models, the multivariate function calculus method, the multivariate function limit method and the function recurrence method have been adopted to research parameter sensitivity differences rules, parameter adjustment directions, parameter adjustment degrees and SEC reserve parameter linkage adjustment rules. The research is significant, because there are great differences between SEC standards and China’s in reserve management mode, reserve estimation method system and financial management system. It is just these differences that cause the frequent adjustment of SEC reserve parameters during the process of SEC reserve submissions each year. As a result, this article reaches some conclusions. Above all, the article has clarified the parameter quantitative conditions that lead to the sensitivity between the SEC reserve and the initial production to begin stronger and weaker than the sensitivity between the SEC reserve and the price in production exponential, hyperbolic and harmonic decline types. Furthermore, the article has clarified the parameter quantitative conditions that lead to the sensitivity between the SEC reserve value and the initial production to begin stronger and weaker than the sensitivity between the SEC reserve value and the price in common production exponential decline types. Moreover, the article has clarified reserve parameter linkage adjustment rules and found the most significant parameter whose least adjustment will cause the largest reserve increase. In addition, the function calculus method adopted to disclose reserve parameter sensitivity rules will expand the parameter sensitivity analysis method that took the previous statistical mapping method as the main analysis method.

Turkish Policy towards the Eastern Mediterranean: a Study in Opportunities and Challenges"

The eastern Mediterranean has emerged more than before since 2010, driven by the large estimates of natural gas reserves in this region, and since this region constitutes a permanent point of conflict between the major powers overlooking it - notably Turkey and Greece - these natural resources have ignited tension In the region again, and brought to the fore many historical contracts that the victorious countries established in the First World War and related to sharing the legacy of the lost Ottoman Empire in that war, and these events prompted the Turkish decision-maker to try to establish its rights there according to a Turkish vision that serves its interests primarily .
 Turkey has many political, economic and military opportunities in this region, driven by its strategic importance, and its military superiority over most of the countries surrounding this region, in addition to an effective foreign policy and deep-rooted relations with many global powers, on the one hand; On the other hand, the magnitude of the challenges facing this region increases with the increasing influence of world powers and their aspiration for economic and strategic gains in the eastern Mediterranean, and this raises the level of the region's importance from regional to global importance.

Reservoir characterization and identification of new prospect in Srikail gas field using wireline and seismic data

Although reservoir characterization has been carried out by many researchers on the sedimentary package of the Bengal basin hydrocarbon province, integration of petrophysical and seismic sequence-based reservoir evaluation is rarely taken into account. This paper focuses on the identification of gas zones, reserve estimation and identification of new prospects in Srikail gas field within the eastern fold belt of Bengal basin integrating four wireline logs and 2D seismic data. Our study finds seven hydrocarbon-bearing zones (A, B, C, D, E, F and G) within the measured depth between 2429.5 and 3501 m. Petrophysical properties of seven hydrocarbon-bearing zones indicate that they are good quality reservoir sands. The gas horizons were mapped on seismic sections which reveal that the NW–SE anticlinal structure is largely affected by channels in the crest and western flank. The channels are infilled by fine-grained sediments which act as cap rock on northern and western parts of the structure. Thus, the anticlinal structure and fine-grained sediments make a potential trap for hydrocarbon accumulation and laterally and vertically well-distributed sequence remnants are the main reservoir rocks in this area. Volumetric reserve estimation of these sands provided a total gas initially in place as 552 billion cubic feet. Moreover, all the four wells are drilled in the southern block of the structure, and since there is a structural continuity from south to the north, it is highly recommended to drill a well up to 3000 m depth in the northern block to test its hydrocarbon potentiality. Overall, the outcomes of this study contribute new insights for reservoir characterization and identification of new prospects in an efficient way.

Impact of Geological Factors on Marine Shale Gas Enrichment and Reserve Estimation: A Case Study of Jiaoshiba Area in Fuling Gas Field

Geological factors are key elements to control shale gas enrichment and influence the accurate estimation of shale gas reserve. However, the impact of the main geological factors, such as porosity, mineralogy, and organic matter, on marine shale gas enrichment and reserve calculation has not yet been fully clarified. Herein, we measured gas adsorption, porosity, mineralogical composition, and total organic carbon content of the marine shale samples from the Jiaoshiba area of Fuling gas field in Sichuan Basin, South China, and investigate the relationships between the geological factors and the adsorbed gas content. The results show that adsorbed gas content is positively correlated with total organic carbon and porosity; the larger specific surface area of samples with more clay minerals essentially contributes to shale gas enrichment. Additionally, the sealing of faults imposes a significant impact on shale gas accumulation. The probability volume method was applied to calculate the shale gas reserve. The reserves of P90 (the most pessimistic reserve), P50 (the most likely reserve), and P10 (the most optimistic reserve) were calculated, respectively, which provides useful information to reduce the risk in shale gas development.

Present Gas Reserve Estimation Using Wireline Logging Data of Habiganj Gas Field, Bangladesh

Habiganj Gas Field (HGF) is one of the most producing and promising gas field in Bangladesh which is ranked as second largest gas field in aspects of Gas Initially In Place (GIIP). It formed by a north south elongated anticline which lies in the northernmost end of the 130km long Baramura anticline from Tripura (India) in the south. This paper shows the present gas reserve estimation with a view of four gas producing wells (i.e. HBJ-7, HBJ-9, HBJ-10, and HBJ-11) in account of upper gas sand has been access via the investigation of lithology, wire line logging data and production data are used as parameter for volumetric method. The average water and gas saturation of the reservoir has also been determined by Archie equation. From the previous analysis with logging data of HGF, it was found that the Gas Water Contact (GWC) was at 1458m and at present it is at about 1415m. The upper gas sand lies at a depth of 1320m below the surface and has a maximum gross pay 230m thick. The gas sand shows average porosity 30% (calculated from the combination of neutron and density porosity logs) and average permeability in the range of 2-4 Darcy’s which indicates an excellent quality reservoir. The water saturation of Habiganj gas sand layer is considered for the depth range of 1330m to 1510m with 5m interval in-deed. Thereafter, water saturation and gas saturation of those wells (HBJ-7, HBJ-9, HBJ-10 and HBJ-11) are 27% and 73%, 29% and 71%, 15% and 85%, and 19% and 81% respectively. The gas formation volume factor (Bg) is estimated at about 0.0075 (rcf/scf) for the average 2053.13psi shut in pressure. From the above discussion it is found that the Gas Initially in Place by HBJ-7, HBJ-9, HBJ-10, and HBJ-11 wells are 5.35Tcf, 4.83Tcf, 5.71Tcf and 5.20Tcf respectively and the cumulative reserve for the HGF is 5.25Tcf while the recoverable reserve is 3.13Tcf. This study would be significant implications for reserve estimation and decision making in an effort to explore the present condition of gas reserve in HGF and the techniques described here can be used in other gas field as a base line for projections of gas reserve.

To What Extent do United Kingdom Companies Provide Oil and Gas Reserves Information Sufficient to Satisfy Statement of Recommended Practice Requirements?

The uncertainty surrounding oil and gas reserves estimation and the cost of gathering reserves data discourage firms from disclosing sufficient data to satisfy SORP (statement of recommended practice) requirements, especially where oil and gas reserves disclosure is discretionary. However, the need to reduce agency cost and signal to stakeholders induces firms to disclose oil and gas reserves. The contrasting views on the rationale guiding the extent of disclosure were examined in this study. A sample was drawn from 83 United Kingdom (UK) oil and gas exploration and production companies listed on the London Stock Exchange. Appropriate statistical tools were used to investigate the extent of oil and gas reserves disclosure. The findings provide mixed results about the extent of disclosure to meet SORP's requirements. There was no particular evidence that UK oil and gas companies provide qualitatively acceptable oil and gas reserves quantity information. The observed varying degrees of disclosure in the market could be attributed to a discretionary regime that allows firms to determine how and when to disclose. Policy makers and industry regulators could find the results useful in assessing the current extent of disclosure compliance.

Analysing the sensitivity of input parameters for oil reserve estimation of DQ oil field in conjunction with Monte Carlo simulations

The Monte Carlo algorithm is used widely in the areas of humanlife, such as currency risk calculations, mathematical probability and statistics, atmospheric research, materials research applications in laser ... In the oil and gas sector, the Monte Carlo algorithm is mostly applied in oil and gas exploration. Worldwide there are many researchs worked on the Monte Carlo algorithm application through oil and gas reserve estimation. In Vietnam, the reserve estimation with the support of simulation software is no wonder, particularly Monte Carlo algorithms have been adopted on the reserve estimation for many years. However, this algorithm is just applied to predict results. The analysis of the influence of each input parameter on the calculation for reserve estimation is quite restricted. Therefore the article refers to the sensitivity analysis of each input parameter for oil reserve estimation of DQ oil field in conjunction with Monte Carlo simulations in the territory of Vietnam in order to improve reliability of the results. Analyzing results the effects of the input parameters to the reserve estimation by volumetric methods in DQ oil field shows there are five effect parameters (Bulk rock volume, initial water saturation, porosity, formation volume factors, the net to gross thickness ratio), porosity which influence range varies from 0.66 ÷ 0.83 is the greatest impact factor to the assessment results.

Investigation of shale gas microflow with the Lattice Boltzmann method

In contrast to conventional gas-bearing rocks, gas shale has extremely low permeability due to its nano-scale pore networks. Organic matter which is dispersed in the shale matrix makes gas flow characteristics more complex. The traditional Darcy’s law is unable to estimate matrix permeability due to the particular flow mechanisms of shale gas. Transport mechanisms and influence factors are studied to describe gas transport in extremely tight shale. Then Lattice Boltzmann simulation is used to establish a way to estimate the matrix permeability numerically. The results show that net desorption, diffusion, and slip flow are very sensitive to the pore scale. Pore pressure also plays an important role in mass fluxes of gas. Temperature variations only cause small changes in mass fluxes. The Lattice Boltzmann method can be used to study the flow field in the micropore spaces and then provides numerical solutions even in complex pore structure models. Understanding the transport characteristics and establishing a way to estimate potential gas flow is very important to guide shale gas reserve estimation and recovery schemes.

A Primer on the Economics of Shale Gas Production Just How Cheap is Shale Gas?

The authors analyze the economics of natural gas production in the U.S. in light of the government's recent dramatic upward revisions in gas reserve estimates as a result of advances in horizontal drilling and fracturing (“fracking”). While some observers believe the U.S. will enjoy very large supplies of low‐priced gas for a long time to come, others are not so sure. Using the data from gas wells completed in the Haynesville shale of northern Louisiana, the authors offer a probabilistic and economic perspective on these newly accessible reserves.Their model and NPV simulations indicate that shale gas exploitation is probably sustainable (with a 60% likelihood), but with some important reservations. NPVs are highly sensitive to gas price assumptions and projected production volumes. The authors' base case assumes the continuation into the foreseeable future of the current gas futures price curve; but the authors also point out that a fall in price of just 17% along that curve would reduce well NPVs to zero. Although it is clear that production from shale wells declines more rapidly than production from conventional wells, engineers have too little history with shale wells to forecast ultimate production with great confidence. Nevertheless, shale gas drilling opportunities also present energy companies with valuable “follow‐on” real options that are not captured in NPV analysis. This additional source of value is inherent in vast shale gas formations in which successful wells tend to lead to more development opportunities.

Gas-to-Liquids Comes of Age in a World Full of Gas

Gas-To-Liquids Developments By the end of the decade, modular gas-to-liquids (GTL) plants distributed around wellheads in places such as North Dakota, USA, and Siberia, Russia, may become commonplace as pressure mounts on producers to monetize marginal natural gas resources. Small-scale GTL plants take the unwanted natural gas that is a byproduct of oil production, known as associated gas, and transforms it into more valuable liquid products. The technology can also be used to produce stranded gas reserves where a lack of distribution infrastructure exists. The current disparity between crude and natural gas prices and the ever-rising estimates of global natural gas reserves are driving oil companies to study the feasibility of using small-scale GTL plants. North America, where the use of hydraulic fracturing has led to a surge in oil and gas production, will likely be the first region to see the widespread adoption of modular GTL technology. With every new oil well that comes online, operators face tighter pipeline constraints, less gas-processing capacity, and increasing scrutiny from both regulators and the public sector on the disposal of associated gas through flaring. The associated gas that bubbles up with the crude is a phenomenon virtually all oil wells experience and, according to a 2011 report published by the World Bank, more than 5 Tcf of this gas is flared annually while another 15 Tcf is estimated to be reinjected. Two companies, CompactGTL and Velocys, are at the forefront of small-scale GTL development, and both have systems designed specifically to address the untapped markets that associated and stranded gas represent. CompactGTL, based in the United Kingdom, has plans to commission its first modular GTL plant in North America by the end of 2016 to produce synthetic crude oil, or syncrude, from natural gas. Syncrude, a milky white substance, is so free of impurities such as sulfur that it can command a premium price over crude oil because of the flexibility it gives refiners to optimize their operations. “There is an enormous amount of interest in North America for this solution,” said Iain Baxter, director of business development at CompactGTL. “The ability to take natural gas at the point of production and convert that into oil there and then—that is an incredibly valuable capability.”

Qualifying Seismic as a "Reliable Technology"—An Example of Downdip Water-Contact Location

Summary The term "reliable technology" was added to the lexicon of oil and gas reserves estimation with the updated regulations published by the US Securities and Exchange Commission in late 2008 (US Securities and Exchange Commission 2008). A previous paper (Sidle and Lee 2010) described an approach to the demonstration that a technology satisfied the criteria of a reliable technology. This paper builds on the use of the scientific method, as described in the previous paper, by examining a real-life example of seismic interpretation to define water contacts downdip of hydrocarbon-column penetrations. Complex technologies, such as seismic, require careful and detailed calibration and testing to demonstrate the consistency and repeatability needed to qualify as a reliable technology. However, this complexity need not preclude that technology from use as reliable. Proper analysis of the science behind the technology and testing to demonstrate those circumstances that allow reliable conclusions from the technology will permit even a complex technology to be qualified as acceptable. The example used is from the Gulf of Mexico (GoM) deep water. It gives the results from several turbidite sand reservoirs in multiple fields to demonstrate the conditions under which certain seismic can be shown as reliable. The learnings from these applications allow the development of a "reliability qualification checklist" that defines the conditions under which the seismic data are definitive. Then, it describes the final testing of the "reliable data" to determine when a seismically interpreted water contact is sufficiently conclusive to be reasonably certain. This paper will provide a useful description of how the qualification of a technology can be planned, tested, and conclusions drawn. It will provide examples of constraints that develop from the theoretical analysis and testing results and show how these constraints can be incorporated into a set of limitations on the application of the technology. While certain elements of the technology are discussed in this paper, it is not the authors’ intent to provide an exhaustive description of the seismic theory and methods used for this example. Rather, the paper will focus on the reliability demonstration process.

Gas-Reserves Estimation in Resource Plays

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 130102, ’Gas-Reserves Estimation in Resource Plays,’ by W.J. Lee, SPE, Texas A&M University, and R.E. Sidle, SPE, Consultant, prepared for the 2010 SPE Unconventional Gas Conference, Pittsburgh, Pennsylvania, 23-25 February. See SPE Econ & Mgmt, October 2010, page 86. The petroleum industry’s lack of understanding of physical properties and the physics that control production from many important resource plays limits the ability to model and forecast production and reserves from these resources with confidence. While measurement technology and modeling accuracy are improving, the industry often is forced to resort to empirical methods that lack the validation usually required for high-confidence results. Some of the procedures in common use for forecasting are reviewed, and key strengths and limitations of the techniques are identified. Introduction Preferably, proper characterization of a resource play begins with production. When attempting to characterize a resource and to forecast production, it is important to know what can and cannot be determined. Thus, pilot tests, resource characterization, and analogs are favored over curve fitting or highly complex reservoir simulation. Analytical models not based on analogs are useful, but only to investigate the generalized incremental effects of different production conditions, such as horizontal vs. vertical wells or completion and well-operation methods. Analogs (usually based on older in-field wells) for decline analysis or type-curve techniques generally would be the preferred methods for high-confidence forecasts and reserves estimates. This approach has proved valuable in examples as diverse as the Antrim shale, Pinedale tight gas, and California diatomite. As a result, high-confidence reserves estimates begin with older wells—wells that have experienced any early-life transient-production effects and have reached a stage in which only stable, long-term trends are the dominant influence on production rate. The considerable complexities of production from resource plays make it important to isolate early effects from those that are fundamental to ultimate recovery. An incomplete understanding of the basic physics of fluid flow and stimulation results in complex-resource plays currently of interest has limited the ability to develop models that provide high confidence, particularly in shales. Because of this lack of understanding, empirical methods take on an unusually important role, but production histories from the most-modern completion and stimulation techniques are limited in duration, causing problems with validation of a forecasting methodology of any kind. The full-length paper provides a detailed critique of the methods used to forecast production and estimate reserves in poorly understood resource plays.

Case Studies Illustrating the Use of Reservoir Simulation Results in the Reserves Estimation Process

Summary Continuous improvements in reservoir simulation software and the availability of high performance computing equipment are making the use of simulation models commonplace for field development and planning purposes. Naturally, this trend has also increased interest in the use of reservoir simulation model results in the oil and gas reserves estimation process. As simulation specialists who work in a primarily reserves-evaluation company, the authors are routinely asked to evaluate, and in many cases incorporate, simulation results in the reserves estimation process. In addition, the authors are required to opine on the approach and tactics used by clients while they incorporate numerical models in their reserves bookings. Because limited published discussion exists on this topic, the purpose of this paper is to provide some examples of the approach used by the authors. We believe this approach to be appropriate and within the spirit of reserves interpretation as used by typical reserves regulatory bodies such as the U.S. Securities and Exchange Commission (SEC). Papers previously published have discussed the use of models in the reserves process, including the evaluation of the models themselves (Palke and Rietz 2001; Rietz and Usmani 2005). In contrast, this paper provides three case studies that illustrate how results from various models have been used to assist in quantifying reserves. Two of the examples are based on history-matched models, while the third focuses on a pre-production reservoir where no adequate history is available and probabilistic methods were incorporated to help understand the uncertainty in the forecasts. While there is no "cookbook" or step-by-step procedure for using simulation results to estimate reserves, the case studies presented in this paper are intended to both show some examples and also spark some debate and discussion. Undoubtedly there will be some disagreement with our techniques, but an open discussion should prove to be beneficial for both reserves evaluators and simulation specialists.

Variability of geochemical properties in a microbially dominated coalbed gas system from the eastern margin of the Illinois Basin, USA

Abstract This study outlines gas characteristics along the southeastern margins of the Illinois Basin and evaluates regional versus local gas variations in Seelyville and Springfield coal beds. Our findings suggest that high permeability and shallow (100–250 m) depths of these Indiana coals allowed inoculation with methanogenic microbial consortia, thus leading to widespread microbial methane generation along the eastern marginal part of the Illinois Basin. Low maturity coals in the Illinois Basin with a vitrinite reflectance Ro ~ 0.6% contain significant amounts of coal gas (~ 3 m3/t, 96 scf/t) with ≥ 97 vol.% microbial methane. The amount of coal gas can vary significantly within a coal seam both in a vertical seam section as well as laterally from location to location. Therefore sampling of an entire core section is required for accurate estimates of coal gas reserves.

A Bootstrap Approach to Computing Uncertainty in Inferred Oil and Gas Reserve Estimates

This study develops confidence intervals for estimates of inferred oil and gas reserves based on bootstrap procedures. Inferred reserves are expected additions to proved reserves in previously discovered conventional oil and gas fields. Estimates of inferred reserves accounted for 65% of the total oil and 34% of the total gas assessed in the U.S. Geological Survey's 1995 National Assessment of oil and gas in US onshore and State offshore areas. When the same computational methods used in the 1995 Assessment are applied to more recent data, the 80-year (from 1997 through 2076) inferred reserve estimates for pre-1997 discoveries located in the lower 48 onshore and state offshore areas amounted to a total of 39.7 billion barrels of oil (BBO) and 293 trillion cubic feet (TCF) of gas. The 90% confidence interval about the oil estimate derived from the bootstrap approach is 22.4 BBO to 69.5 BBO. The comparable 90% confidence interval for the inferred gas reserve estimate is 217 TCF to 413 TCF. The 90% confidence interval describes the uncertainty that should be attached to the estimates. It also provides a basis for developing scenarios to explore the implications for energy policy analysis.