Porosity is a key parameter in shale gas reservoir evaluation and reserve calculation and its accurate test is the basis for calculating geological reserves of shale gas and determining development ...plans. In order to clarify the differences between different porosity test methods and their influences on the calculation results of shale gas reserves, we collected 65 shale samples of Lower Silurian Longmaxi Formation from six shale gas wells in the Zhaotong National Shale Gas Demonstration Area of the southern Sichuan Basin for comparative experiments using three porosity test method, including gas injection porosimetry (GIP) method, water immersion porosimetry (WIP) method and nuclear magnetic resonance (NMR) method. Then, these three methods were comparatively analyzed based on the test results. Finally, it was proposed to optimize the key parameters of these three shale porosity test methods. And the following research results were obtained. First, in terms of the GIP method, the particle size of shale sample shall be in the range of 20–60 mesh and the helium saturation equilibrium time shall be over 1800 s. Second, in terms of the WIP method, the sample shall be dried for at least 48 h under 110 °C and saturated for 24 h under the confining pressure of 15 MPa. Third, in terms of the NMR method, NMR porosity calculation shall not be conducted until the NMR signal of the dried sample is deducted, on the basis of echo time and waiting time optimization. Fourth, porosity average and median value obtained by these three shale porosity test methods follow the relationship of WIP porosity > NMR porosity > particle GIP porosity > plunger GIP porosity. Fifth, different shale porosity test methods have greater influences on the calculation results of shale gas geological reserves, whose difference can reach 20%. In conclusion, during the application of NMR method and WIP method, fluid is introduced for saturation, which may damage the shale pores. However, the particle GIP porosity can reflect the entire space of shale more comprehensively and is not influenced by the properties of the applied fluid. Therefore, it is suggested to adopt the particle GIP method to calculate shale gas geological reserves.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
To improve the accuracy of the calculation for the current mineral resource reserves, a calculation method for mineral resource reserves based on multi-point geostatistics was proposed. The new ...method, including four major steps, focuses on calculating resource reserves of ore body accurately for rational development and utilization of mineral resources. To represent the spatial geometric relationship of the ore body accurately, a three-dimensional irregular tetrahedron voxel (3D ITV) model construction method for the ore body is proposed first. Second, a tetrahedron voxel grade model built by the mineral reservation calculation oriented multi-point geostatistics method is proposed. The construction of 3D training image, definition of data template with N-order adjacency voxels, construction of search trees and conditional probability extraction of data event are conducted in this step. Finally, the resource reserves of the ore body are calculated on the basis of the tetrahedron voxel grade model. A calculation experiment of copper reserves is conducted to demonstrate the validity of the new method. The new method can be meaningful to the exploration, development, and utilization of mineral resources.
Reserve evaluation is the core of asset value evaluation of new investment projects in overseas oil and gas field development and determines the investment income and formulation of a development ...plan. A method of reserve evaluation was established by using geological modeling in order to reasonably and quickly evaluate the reserves of new investment projects in overseas oil and gas field development, and to provide a basic geological model for the formulation of a development plan. The evaluation consists of data collection, geological framework evaluation, reservoir facies and properties evaluation, and reserve calculation and risk assessment. It can be divided into two stages: geological modeling and reserve evaluation. The geological modeling stage includes three-dimensional modeling of the most probable structures, reservoir facies and properties based on data collection. In the reserve evaluation stage, the uncertainty of the geological framework, reservoir facies and properties are carried out based on
In the modern rapidly evolving society, the science and the business are facing new needs and challenges constantly. The insurance industry and its mathematical foundation, the actuarial science, are ...not exceptions. Currently, the greatest challenge that the insurance system has to cope with is the issue of the new international financial standard that affects the calculation of reserves among other things. So far, insurers have mainly used common classical deterministic methods. However, the new standard emphasizes the necessity of the realistic prognosis that is best achieved with stochastic modelling tools since deterministic models do not represent the uncertainty and the random nature of future possible losses. This article considers the advantage of using stochastic modelling for reserve calculation in comparison to the deterministic approach.
The article consists of five sections.
In the first section, we briefly present the technique that lies in the basis of technical reserves calculation.
The second section is devoted to such deterministic methods of reserve calculation as the Bornhuetter-Ferguson method and the chain-ladder method.
In the third section, we consider modifications of two stochastic models – the Mack method and the bootstrapping technique.
The fourth section considers the adjustment of reserves for the time value of money and inflation.
In the fifth section, the results of modelling in the programming language R are presented.
This study aims to compare two approaches for the reserve calculation of cement raw material by geological sections and structural maps. The first is legally based, and its accuracy is approved by ...periodical calculation of the exploited material on site. In this research, it was crucial to determine deviation in the calculation approach, i.e., geological section volume calculation versus the volume obtained as a software solution estimated as a number of cells between two structural maps, i.e., maps interpolated at the top and bottom of the analysed lithological unit. Due to complex mineralogy, raw cement needs different energy consumption that directly affects the procedure of cement production, e.g., increases in air pollution through CO2 emissions. The research area was the exploitation field “St. Juraj–St. Kajo,” situated near the town of Split, region of Dalmatia, Southern Croatia. In the deposit, there are seven different lithological units, and all were technologically divided based on their chemical compounds. The lithology included dominantly marl and sandstone with occasional alternations of the conglomerate. Although in the geological sense it is considered a single unit, it partially contains interlayers in the form of lenses such as limy (calcitic) marl, clacisiltite (clayey limestone), and clayey marl. Generally, the knowledge of interlayers’ existence is more important than their exact quantity because it affects expectations of a nonuniform material’s technological quality at the location. For the purpose of the analysed lithological unit calculation, the volumes of the interlayers within were determined as well. Using geological sections for volume calculation is based on the calculation of the block volume (V) between two parallel vertical sections (P1, P2), which is obtained as a product of the mean areas (Paverage) of adjacent parallel sections (P1, P2) multiplied by the distance between them (d). Structural maps represent the calculation of the volume of the analysed object under a function f (x, y) defined by a double definite integral. Comparison of research results encourages the use of software solutions for the volume calculation of cement raw material volume in the future.
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To accurately obtain the geological reserves of fracture-cavity carbonate reservoirs, the material foundation of the reservoir should be implemented. Based on the conventional material balance ...formula of the reservoir, the material balance equation of four types of oil-water models: closed constant volume non-aqueous fracture-cavity unit, non-closed water body with intrusive fracture-cavity unit, closed water body fracture-cavity unit, closed water body and water invasion fracture-cavity unit is introduced. In view of the particularity of fracture-cavity reservoirs, the percentage of closed water of the total volume of fracture-cavity is introduced. The two parameters that have less influence on the calculation results, such as the bound water saturation and rock compression coefficient, are removed. The formula for calculating the material balance of fracture-cavity reservoirs under the 4 types of oil-water model was re-derived. At the same time, in order to improve the accuracy of the calculation of the material balance formula, when calculating the compression coefficient and volume coefficient of crude oil, the method of linear fitting will be used to introduce the sensitive parameter of pressure change to establish the relationship between the compression coefficient and the volume coefficient of crude oil and the gas-oil ratio and pressure, respectively. Taking the Halaha-tang fracture-cavity oil field as an example, the calculation results show that the average error between the fitting results of the compression coefficient and volume coefficient of the crude oil and the laboratory measurement results is 4.7% and 1.9%, respectively, which can more accurately calculate abnormal high pressure and deficient reservoirs reserves. The newly derived fracture-cavity reservoir material balance formula is more suitable for the calculation of reserves in fracture-cavity type reservoir.
To avoid big deviation in reserve estimation and make scientific and reasonable reserves to guide the exploration and development of fracture-cavity carbonate reservoirs, a new three-dimensional ...reservoir space description and reserve calculation method for layered, fracture-cavity carbonate reservoirs is used to calculate the reserves of X block in the Halahatang oilfield in the Tarim Basin. In the method, the reserve calculation parameters are worked out by quantitative spatial delineation based on high precision three-dimensional seismic data; the high confidence well-seismic inversion and sensitive attributes and threshold value are used jointly to delineate the oil-bearing area, effective thickness and effective porosity of the cavity, vug and fracture reservoirs. The reserves are calculated with the volumetric method, and the dynamic recovery of different types of reservoirs is calibrated by actual drilling data. This method is suitable for reserve estimation and development program making of fracture-cavity carbonate reservoirs with strong heterogeneity.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
As the formation pressure drops during the development process of shale gas reservoir, the effects of stress sensitivity and matrix shrinkage occur. Stress sensitivity effect decreases the porosity ...of reservoir formation, while matrix shrinkage effect increases the porosity. Therefore, the porosity will be influenced by the combined effect of both stress sensitivity and matrix shrinkage, which need to be considered in the material balance equation of shale gas reservoir. In this work, based on the material balance theory of shale gas reservoir, a material balance equation considering the influences of stress sensitivity and matrix shrinkage on shale gas reservoir that the porosity varies as formation pressure changes is established. Then, the material balance equation is linearized, and the original gas in-place (the controlled reserve) of single well can be calculated by the intercept and the slope of the straight line of the linearized material balance equation, which is convenient for field application. Production data of three gas wells of a certain shale gas reservoir are calculated with the proposed material balance equation in this work. The calculation results indicate that the stress sensitivity effect has the dominant influence on the porosity at the early stage of formation pressure dropping, while the matrix shrinkage effect dominates the influence on the porosity at the late stage of formation pressure dropping. Furthermore, the controlled reserves of the three gas wells have decreased by considering the effects of stress sensitivity and matrix shrinkage in the material balance equation.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Most of the initial in-place and undeveloped OOIP are low-grade reserves, and how to evaluate their potential is an urgent problem. There are many uncertainties in low-grade reserves, such as complex ...geological conditions, strong reservoir heterogeneity, limited data and limited geological knowledge. The reliability of the conventional evaluation method is poor. Therefore, a series of systematic evaluation methods for initial in-place and undeveloped OOIP on the basis of quantitative uncertainty was proposed, which mainly focused on three improvements. Firstly, the range value was used to describe the uncertainty of OOIP, which changed the unique value estimated by the certainty method in the past. The degree of certainty was proposed to quantitatively characterize the risk of reserves. Secondly, the evaluation index system, the evaluation method and the evaluation process of uncertainty of the key parameters were established. Thirdly, the new method was changed from the previous emphasis on reserve scale to
Pore sizes are typically on the order of nanometers for many shale and tight rock oil reservoirs. Such small pores can affect the phase behavior of in situ oil and gas owing to large capillary ...pressure. Current black-oil simulation practice is to alter the unconfined black-oil data for a fixed mean pore size to generate confined black-oil data with a suppressed bubble-point pressure. This approach ignores compositional effects on interfacial tension and the impact of pore-size distribution (PSD) with variable phase saturations on capillary pressure and phase behavior.
In this paper, we develop a compositionally-extended black-oil model where we solve the compositional equations (gas, oil, and water components) directly so that black-oil data are a function of gas content in the oleic phase and gas-oil capillary pressure. The principle unknowns in the variable bubble-point fully-implicit formulation are oil pressure, overall gas composition, and water saturation. Flash calculations in the model are non-iterative and are based on K-values calculated explicitly from the black-oil data. The advantage of solving the black-oil model using the compositional equations is to increase robustness of the simulations owing to a variable bubble-point pressure that is a function of two parameters; gas content and capillary pressure. Leverett J-functions measured for the Bakken reservoir are used to establish the effective pore size-Pc-saturation relationship, where the effective pore size depends on gas saturation, which is the non-wetting phase saturation. The input fluid data to the simulator, e.g. interfacial tension (IFT), phase densities and viscosities, are pre-calculated as functions of pressure from the Peng-Robinson equation of state (PREOS) for three fixed pore sizes. During the simulation, at any pressure and saturation, fluid properties are calculated at the effective pore radius by using linear interpolation between these three data sets. We compare the results of the compositionally-extended black oil model with those of a fully-implicit eight-component compositional model that we have also developed. The results for the Bakken reservoir show that including PSD in the model can increase estimated recoveries by nearly 10% for initially undersaturated reservoirs while the increase can be over 100% for initially saturated reservoirs. Capillary pressure significantly increases the original oil-in-place (OOIP) for reservoirs that would otherwise be initially saturated leading to larger oil production.
•The new black oil model is robust, and easy to implement using the compositional approach. The model could also be easily used for volatile-oil or gas condensates, although here we focus solely on the black oil of the Bakken.•Primary recoveries increase when the effect of capillary pressure on phase behavior is included. The increase is in the range of 5 – 10% OOIP for the cases considered where the initial reservoir pressure is above the bubble-point pressure. Primary recoveries increase substantially (by over 100% for some cases) when the initial reservoir pressure is below the bubble-point pressure and capillary pressure effects on flash calculations are included.•The change in black-oil properties (densities, viscosities, solution gas-oil ratio, volatile oil-gas ratio) is nearly linear with pore curvature thus, linear interpolation is reasonably accurate.•The recoveries and pressures agree well to those of detailed fully-compositional simulations with and without the effect of capillary pressure on phase behavior.•Using the pore-size distribution (PSD) is more accurate than applying a fixed-pore size approach as is current practice. The increase in recoveries with capillary pressure included in flash calculations decreases somewhat using PSD.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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