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Aiming at the disadvantages of the brittleness index commonly used in oil/gas exploration, this article proposed two new brittleness indexes (elastic brittleness and mineral brittleness) in order to predict brittle shale distribution accurately: the former index, based on elastic parameters (Young's modulus and Poisson's ratio), characterizes the o...
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... to the elastic property RBI proposed in this paper, the brittleness of each major mineral in shale is considered different, quartz highest, and kerogen lowest. So the brittleness factor of quartz is assumed as 1 and that of kerogen as 0, then the brittleness of main minerals (14 kinds in this paper) in the shale is obtained by normalization. Fig. 4 shows the brittleness factor of 14 minerals. The brittleness factors in descending order are: quartz, dolomite, calcite, natronite, narolite, anhydrite, perthite, albite, halite, orthoclase, Gulf clay, mixed clay, kerogen, and kaolinite. On this basis, a new mineral RBI based on the brittleness factor of each kind of mineral is ...
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... Mandal et al. (2022) defined the mechanical brittleness index based on the peak strain and the postpeak slope gradient. Although the method of evaluating reservoir brittleness through triaxial compression tests on cores is generally considered to be the most reliable, the method is difficult to widely use in the field due to the limited coring length that is possible on site as well as the long time expenditure and high financial cost of conducting the triaxial compression test evaluation method (Liu and Sun 2015). ...
Deep shale reservoirs (3500–4500 m) exhibit significantly different stress states than moderately deep shale reservoirs (2000–3500 m). As a result, the brittleness response mechanisms of deep shales are also different. It is urgent to investigate methods to evaluate the brittleness of deep shales to meet the increasingly urgent needs of deep shale gas development. In this paper, the quotient of Young’s modulus divided by Poisson’s ratio based on triaxial compression tests under in situ stress conditions is taken as SSBV (Static Standard Brittleness Value). A new and pragmatic technique is developed to determine the static brittleness index that considers elastic parameters, the mineral content, and the in situ stress conditions (BIEMS). The coefficient of determination between BIEMS and SSBV reaches 0.555 for experimental data and 0.805 for field data. This coefficient is higher than that of other brittleness indices when compared to SSBV. BIEMS can offer detailed insights into shale brittleness under various conditions, including different mineral compositions, depths, and stress states. This technique can provide a solid data-based foundation for the selection of ‘sweet spots’ for single-well engineering and the comparison of the brittleness of shale gas production layers in different areas.
... Prediction methods for rock physics and brittleness can generally be categorized into three types: 1) brittleness prediction based on rock mineral composition, which calculates the brittleness index profile for the entire well section using the mineral composition, achieving a high level of accuracy (Mukerji et al., 1995;Zhi and Zan, 2015;Li et al., 2019;Ma et al., 2019;Ba et al., 2021;Meng et al., 2021); 2) brittleness evaluation based on rock mechanical elastic parameters, relying on vertical and horizontal well logging wave data and pre-stack inversion. It employs the Rickman formula to compute the correlation between Young's modulus, Poisson's ratio, and the brittleness index (Meng et al., 2015;Li et al., 2017;Gui et al., 2023); 3) utilization of uniaxial and triaxial stress-strain tests on core samples to obtain correlations between rock physical parameters, mineral composition, bedding characteristics, hydrocarbon content, and other parameters (Wang et al., 2017;Chen et al., 2019;Tao et al., 2020;Liu et al., 2021). ...
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... (Loseth et al. 2011). Seismic reflection can be used to predict source rocks by geophysical inversion and seismic stratigraphy (Charles 1977;Dong et al. 2014;Liu and Sun 2015;Samakinde et al. 2021;Mahlalela et al. 2021;Liu et al. 2007;Cao et al. 2009;Freedman et al. 2018;Gentzis 2016). Therefore, the use of geophysics technology to predict source rocks has received increasing attention from geoscientists. ...
The Lishui Sag, located in the East China Sea shelf basin, is one of the most promising offshore oil and gas exploration areas in China. Drillings in recent years have yielded unsatisfactory results. Characterizing source rocks in oil and gas exploration in the whole study area can help to find targets that may contain oil. However, the knowledge of source rocks is limited to a few locations of previous drillings. Therefore, we proposed integrating borehole (sedimentary facies) and seismic data to determine the location and thickness of the source rocks in the Lishui Sag, China. The results show that source rocks are mainly distributed in the Yueguifeng and Lingfeng Formations. There are fewer source rocks in the East Subsag and South Subsag, and the thickness is less than 200 m. The thickness of source rocks in the Lishui Sag near well W2 is the thickest, reaching 500 m. By comparing the other studies, we believe that the combination of geophysics with sedimentary facies is an effective method for the determination of source rock thickness in the East China Sea Shelf Basin. This method can be extended to other basins lacking boreholes.
... The Aki-Richards approximation and the BI-Zoeppritz equation have been developed to extract the brittleness index directly from seismic data. Empirical formulas based on Young's modulus and Poisson's ratio, such as Eqs 1, 2, are commonly used for brittleness calculations, but they have limitations (Luan et al., 2014;LIU and SUN, 2015). ...
This paper presents a novel Bayesian-based method for predicting brittleness. The method involves synthesizing petrophysical data from multiple well cores to establish a joint Gaussian distribution function for shale facies and non-shale facies. Furthermore, Bayesian facies classification is applied to seismic data. The proposed method combines non-shale facies data with Rickman brittleness data to obtain a new brittleness index. The joint Gaussian distribution function and Bayesian classification are utilized to enhance the differentiation of brittleness among different geological bodies. Practical data analysis demonstrates that the new brittleness index effectively increases the contrast in brittleness values between various geological bodies, highlighting target areas of interest. The presented method offers a promising approach for brittleness prediction, leveraging the integration of petrophysical and seismic data through Bayesian techniques. The results suggest its potential applicability in enhancing the characterization and understanding of geological formations.
... Hucka and Das [17] calculated rock brittleness using compressive and tensile strengths through uniaxial compressive strength and Brazilian testing. Later, many scholars used rock mechanical parameters and rock brittle mineral content to characterize rock brittleness and believed that horizon rocks with large brittleness indexes were more prone to fracture and formed a complex fracture network; therefore, the perforation location was optimized according to the brittleness index [18][19][20]. Presently, there are three types of methods for evaluating rock brittleness: mineral composition, mechanical parameters, and stress-strain parameters [21]. ...
To solve engineering problems in the production process after fracturing and flooding of low-permeability sandstone reservoirs, such as rapid water-cut rise and low water flooding efficiency, a method for optimizing the fracture parameters of low-permeability sandstone reservoirs under fracturing flooding conditions was proposed. A rock property test experiment was first carried out, the fracturing coefficient was defined, and an evaluation method for the brittleness index of low-permeability sandstone was established to optimize the perforation location of the fracturing reservoir. A productivity numerical model for the two-phase flow of oil–water in matrix–fracture media was established to optimize the fracture morphology under fracturing flooding conditions. The results showed that the quartz content, Young’s modulus, and peak stress mainly affected the fracturing coefficient of rock and are the key indicators for evaluating the brittleness of low-permeability sandstone reservoirs. For production wells in the direction of minimum horizontal principal stress, the swept area of water flooding should be expanded, fracture length should be optimized to 90 m, and fracture conductivity should be 20 D·cm. For fracturing production wells in the direction of maximum horizontal principal stress, the advancing speed of the water injection front should be slowed down to reduce the risk of water channeling in injection-production wells. The optimized fracture length was 80 m, and the fracture conductivity was 25 D·cm. The application of these findings can markedly improve oil production and provide a reference for optimizing the fracture parameters of low-permeability sandstone reservoirs under fracturing flooding conditions.
... At present, researchers have established various brittleness evaluation indicators in terms of rock mineral composition and porosity [11][12][13][14][15][16], rock strength parameter [17][18][19][20][21], Young's modulus and Poisson's ratio [22][23][24], hardness and fracture toughness [25][26][27], impact penetration test [28], acoustic emission characteristics [29][30][31][32], etc. An effective and direct method to evaluate rock brittleness is by using characteristic parameters from full stress-strain curves obtained from laboratory mechanical experiments. ...
As a basic mechanical property of rocks, brittleness is closely related to the drillability, wellbore stability, and rockburst characteristics of reservoir rocks. Accurate evaluation of rock brittleness is of great significance for guiding oil and gas production and reservoir reconstruction. This paper systematically introduced the commonly used brittleness evaluation methods based on the stress–strain curve and analyzed their theoretical background and mathematical models. Combined with practical engineering application, the characterization effect of commonly used brittleness indexes in various rock samples is verified and optimized, and it is obtained that the brittleness index (B17 in this paper), based on the stress–strain curve and considering energy conversion, has the best characterization result for rock brittleness, which has good differentiation for different rock samples. At the same time, considering that the stress–strain curve under high confining pressure may result in a significant yield plateau phenomenon before and after the peak strength, the endpoint of the plastic yield plateau is used to replace the peak point as the starting point for the drop of bearing capacity. The revised brittleness index is consistent with the changing trend of the original curve, which verifies the reliability of the model. Finally, the method for characterizing the brittleness of Class II curves is supplemented, and the combined brittleness index of rock is established, which verifies the rationality and correctness of the index and provide a more general evaluation method for rock brittleness in engineering.
... In shale reservoirs, brittle shale breaks easily during fracturing and forms complex fractures, whereas plastic rocks are less prone to fracture due to plastic changes or artificial fractures in the closing stage due to proppant embedding, resulting in a decrease of fracture conductivity [10]. There are numerous brittleness evaluation methods [11,12], that have emerged recently which include brittleness evaluation methods based on mineral components [13][14][15], rock mechanical parameters [7,16], and stress-strain curve characteristics [17,18] or an evaluation method that combines the above methods [19,20]. There are several approaches for characterizing brittleness, however not all strata will respond to the same method. ...
Due to a great increase in the plasticity of deep marine shale reservoirs in southern Sichuan under high-temperature and high-pressure conditions, the single brittleness evaluation method is difficult to effectively characterize its fracability, which significantly limits the selection of sweet spots and fracturing reconstruction in the area. In the case of the deep marine shale reservoir of the Wufeng-Longmaxi formations in the southern Sichuan Basin, through triaxial high-temperature and high-pressure experiments, fracture toughness and X-ray diffraction experiments, the mechanical properties and its influencing factors in the shale reservoir are studied, and the rock fracture morphology under various loading conditions is quantified. According to the morphological characteristics of shale, the analysis of influencing factors and comprehensive quantitative evaluation of the brittleness has been carried out. The deep marine shale resource in the southern Sichuan Basin is likely to be characterized by its high elastic modulus and low I fracture toughness. The mineral composition, temperature, pressure, and degree of bedding development are the primary factors for determining the brittleness; with high quartz mineral content (>50%), low confining pressure (
... The higher the ratio, the more brittle the rock [7][8][9][10]. The second is based on the stress-strain curve of the rock [11][12][13][14]. The third method uses elastic parameters such as elastic modulus and Poisson's ratio to evaluate rock brittleness. ...
Shale is a special kind of rock mass and it is particularly important to evaluate its brittleness for the extraction of gas and oil from nanoporous shale. The current brittleness studies are mostly macro-evaluation methods, and there is a lack of a micro-brittleness index that is based on nanoindentation tests. In this paper, nanoindentation tests are carried out on the surface of shale to obtain mechanical property, and then a novel micro-brittleness index is proposed. Drawing a heat map by meshing indentation, the distribution characteristics of the brittleness index for the surface of shale and the variation laws between the mineral and brittleness index are explored. The results showed that the dimensionless brittleness index involved parameters including indentation irreversible deformation, elastic modulus, hardness and fracture toughness. The micro-brittleness index of the shale ranged from 7.46 to 65.69, and the average brittleness index was 25.837. The brittleness index exhibited an obvious bimodal distribution and there was great heterogeneity on the surface of shale. The crack propagation channels were formed by connecting many indentation points on the shale surface with high brittleness. The total brittleness index of quartz minerals was high, but the cementation effect with different minerals was various. Although the general brittleness of clay was low, the high brittleness index phenomenon was also exhibited. Studying the micro-brittleness of shale provides a more detailed evaluation for the shale friability, which is used to determine the optimal shale oil and gas recovery regime.
... In contrast, clay minerals have the lowest modulus of elasticity. 59 Particularly, the mixed layered shale containing montmorillonite−illite has a lower Young's modulus. Therefore, in the mineralogical ternary diagram, quartz, pyrite, and carbonate belong to the same type, and feldspar and clay minerals are another two types. ...
To understand the characteristics of variation in porosity and permeability, the physical properties of the shale reservoir under different stress conditions play an important role in guiding shale gas production. With the shale of the Wufeng-Longmaxi Formation in the south of the Sichuan Basin as the research object, stress-dependent porosity and permeability test, high-pressure mercury injection, and scanning electron microscope test were performed in this study to thoroughly analyze the variation in physical properties of different shale lithofacies with effective stress. Besides, the stress sensitivity of different lithofacies reservoirs was evaluated by using parameters such as pore compressibility coefficient (PCC) and porosity sensitivity exponent (PSE), while the optimized support vector machine (SVM) algorithm was adopted to predict the coefficient of reservoir porosity sensitivity. According to the research results, the porosity and permeability of shale reservoirs decline as a negative exponential function. When the effective stress falls below 15 MPa, the damage rate of permeability/porosity increases rapidly with the rise of effective stress. By contrast, the permeability curvature of the shale reservoirs plunges with the rise of effective stress. It was discovered that a higher siliceous content results in a higher permeability curvature of shale, indicating the greater stress sensitivity of the reservoir. The ratio of matrix porosity to microfracture porosity determines the PSE, which is relatively low, and low aspect ratio pores contribute to high porosity compressibility and stress sensitivity. Young's modulus shows a negative correlation with pore compressibility and a positive correlation with Poisson's ratio. High clay minerals have a large number of low aspect ratio pores and a low elastic modulus, which leads to both high PCC and low PSE. Based on the principal component analysis, a multiclassification SVM model was established to predict the PSE, revealing that the accuracy of the sigmoid, radial basis function (RBF), and linear kernel function is consistently above 70%. According to error analysis, the accuracy can exceed 80% with the RBF kernel function and appropriate penalty factor. The research results serve to advance the research on the parameters related to overburden pressure, porosity, and permeability. Moreover, the optimized SVM algorithm is applied to make a classification prediction, which provides a reference for shale reservoir exploration and development both in theory and practice.
... This is performed based on the rock physics model of organic-rich shale. 23 7.2. Impact of Kerogen in Brittleness Index. ...
Measuring the mechanical properties of kerogen, the predominant constituent of organic matter in shale is exceedingly difficult as it constitutes small-scale aggregates interspersed in rocks. Kerogen is characterized by significantly lower stiffness compared to inorganic minerals, thereby the kerogen regions are potential areas for study during, for example, drilling or macroscopic fracture propagation in the course of hydraulic fracturing. For instance, the elastic modulus of kerogen-rich spots is around 10 GPa, while it is about 70 GPa for quartz. Failure of the kerogen nanocantilever beam shows an elastic strain-hardening behavior, indicating a higher energy requirement to propagate a crack. Studies illustrated that the kerogen's mechanical properties are controlled by maceral composition and are positively correlated to the maturity level. This paper provides a comprehensive review of how the mechanical properties of kerogen are elucidated experimentally and contrast the results with the properties delineated from molecular simulation. In addition, we relate kerogen innate attributes, such as maturity and type, to the physical qualities measured and substantiate why accurate knowledge of the mechanical characteristics is pivotal from a hydraulic fracturing perspective.
