Shale Gas Reservoir Evaluation Research Articles

Formation and evolution of shale overpressure in deep Wufeng-Longmaxi Formation in southern Sichuan basin and its influence on reservoir pore characteristics

In the deep Longmaxi Formation shale gas reservoirs of the southern Sichuan Basin, strong overpressure is universally developed to varying degrees. However, there is currently a lack of in-depth research on the formation mechanisms, evolutionary patterns, and the controlling effects on reservoir pore characteristics of strong overpressure. This limitation significantly restricts the evaluation of deep shale gas reservoirs. This study selected typical overpressured shale gas wells in Yongchuan, Luzhou, and Dazu areas as research subjects. Through comprehensive methods such as log analysis, fluid inclusion analysis, and numerical simulation, the dominant mechanisms of strong overpressure formation were determined, and the pressure evolution from early burial to late strong uplift was characterized. Additionally, the impact of varying degrees of overpressure on reservoir pore characteristics was studied using techniques such as scanning electron microscopy, gas adsorption-mercury intrusion, and helium porosity testing. The research findings indicate that hydrocarbon generation expansion is the primary mechanism for strong overpressure formation. The pressure evolution in the early burial phase is controlled by the processes of kerogen oil generation and residual oil cracking into gas. The reservoir experienced three stages: normal pressure (Ordovician to Early Triassic), overpressure (Early Triassic to Early Jurassic), and strong overpressure (Early Jurassic to Late Cretaceous), with pressure coefficients of approximately 1.08, 1.56, and 2.09, respectively. During the late strong uplift phase, the adjustment of early overpressure occurred due to temperature decrease and gas escape, leading to a decrease in formation pressure from 140.55 MPa to 81.63 MPa, while still maintaining a state of strong overpressure. Different degrees of strong overpressure exert a significant control on the physical properties of shale reservoirs and the composition of organic matter pores. Variations exist in the organic matter pore morphology, structure, and connectivity within the deep Wufeng-Longmaxi shale. Higher overpressure favors the preservation of organic large pores and reservoir porosity. Under conditions of strong overpressure development, deep siliceous shales and organically rich clay shales exhibit favorable reservoir properties. By determining the dominant mechanisms of strong overpressure in the Wufeng-Longmaxi Formation and studying pore characteristics, this research not only deepens the understanding of the geological features of deep shale gas reservoirs but also provides a new perspective for understanding the overpressure mechanisms and reservoir properties of deep shale gas reservoirs. Moreover, it is of significant importance for guiding the exploration and development of deep Longmaxi shale and provides valuable references for further research in related fields.

Intelligent Identification and Quantitative Characterization of Pores in Shale SEM Images Based on Pore-Net Deep-Learning Network Model

Among the various shale reservoir evaluation methods, the scanning electron microscope (SEM) image method is widely used. Its image can intuitively reflect the development stage of a shale reservoir and is often used for the qualitative characterization of shale pores. However, manual image processing is inefficient and cannot quantitatively characterize pores. The semantic segmentation method of deep learning greatly improves the efficiency of image analysis and can calculate the face rate of shale SEM images to achieve quantitative characterization. In this paper, the high-maturity shale of the Longmaxi Formation in the Changning area of Yibin City, Sichuan Province, and the low-maturity shale of Beibu Gulf Basin in China are studied. Based on the Pore-net network model, the intelligent identification and quantitative characterization of pores in shale SEM images are realized. The pore-net model is improved from the U-net deep-learning network model, which improves the ability of the network model to identify pores. The results show that the pore-net model performs better than the U-net model, FCN model, DeepLab V3 + model, and traditional binarization method. The problem of low accuracy of the traditional pore identification method is solved. The porosity of SEM images of high-maturity shale calculated by the pore-net network model is between 12 and 19% deviation from the experimental data. The calculated porosity of the SEM image of the low-maturity shale has a large deviation from the experimental data, which is between 14 and 47%. Compared with the porosity results calculated by other methods, the results calculated by pore-net are closer to the true value, which proves that the porosity calculated by the pore-net network model is reliable. The deep-learning semantic image segmentation method is suitable for pore recognition of shale SEM images. The fully convolutional neural network model is used to train the manually labeled shale SEM images, which can realize the intelligent recognition and quantitative characterization of the pores in the shale SEM images. It provides a certain reference value for the evaluation of shale oil and gas reservoirs and the study of other porous materials.

Novel method for total organic carbon content prediction based on non-equigap multivariable grey model

Predicting total organic carbon content plays a crucial role in shale gas reservoir evaluation. To address multi-variable, imperfect logging data and non-equigap characteristics, this study developed a multi-variable grey derivative model for predicting the total organic carbon content trend. To begin with, the non-equigap factor is introduced and the parameter identification of the new model is established on the basis of least square method. Then, to reduce fluctuations in the original data, the weighted geometric average weakening operator is introduced. In addition, considering the system stability, the derivation method is used to calculate the time response formula of the model. Furthermore, two validation cases are provided to verify the validity of this novel model. Finally, the model is applied to the Fuling shale gas field in China for practical forecasting. Compared to other models, such as the grey model, statistical model, and artificial intelligence model, the proposed model achieved higher prediction accuracy in the three cases. Specifically, this model obtained 95.62%, 95.88% and 94.55% prediction accuracy for total organic carbon content. Results that the new model effectively addresses the limitations of previous studies that focus on single-parameter or equal spacing issues.

Study on Seepage Characteristics and Capacity Evaluation of Shale Gas Reservoirs

Study on Seepage Characteristics and Capacity Evaluation of Shale Gas Reservoirs

Coupling effects of temperature, confining pressure, and pore pressure on permeability and average pore size of Longmaxi shale

AbstractThe evolution due to temperature and pressure of shale reservoir permeability affects the productivity evaluation and development decision of shale gas reservoirs, which is very important for the exploration and development of unconventional gas reservoirs. This study analyzed the coupling effects of temperature (25, 50, and 75°C), effective stress (15 and 30 MPa), and pore pressure (0.5, 2.0, 4.0, and 8.0 MPa) on the permeability of the shale sample in the Longmaxi Formation. As the temperature and pressure increased, the apparent permeability exhibited a downward trend, and the absolute permeability decreased with the rise of temperature or effective stress. An in‐depth analysis of the gas slippage factors under the conditions of different temperature and pressure was conducted to evaluate the trend of the average pore width with temperature and pressure. The results were then verified by scanning electron microscopy (SEM). The results provide new insights into evaluating the permeability of the Longmaxi shale and can be used to enhance the gas recovery rate of deep shale gas reservoirs.

Multiparameter Logging Evaluation of Chang 73 Shale Oil in the Jiyuan Area, Ordos Basin

The accurate evaluation of shale oil and gas reservoirs is of great significance to the integrated development of geology and engineering. Based on the core analysis, conventional logging, and array acoustic logging data, the total organic carbon, hydrocarbon generation potential, brittleness, and anisotropy of shale reservoirs were calculated. The p-wave time difference curves calculated by the artificial neural network (ANN) method and the conventional logging curve fitting method were compared. The multiresolution graph-based clustering (MRGC) method was used to classify shale reservoirs into three categories and evaluate the classification results. Brittle minerals such as quartz and feldspar were mainly found to be present in shale reservoirs and clay minerals which mainly consisted of illite. The Chang 73 reservoir is rich in organic matter and has great potential for survival. The p-wave time difference calculated by the fitting formula of the shear wave time difference meter demonstrated high accuracy and did not require a complex ANN model. MRGC method can well classify shale reservoir types. The classification results reduce the interference of human factors and are more scientific and reasonable. This research method is of great significance for the scientific classification and evaluation of shale reservoirs.

Experimental investigation of thermodynamic and kinetic behaviors from water vapor adsorption on four typical clay minerals

Clay minerals within the shale reservoirs mainly exist in the water-bearing state in situ. The water adsorption behavior and behind mechanisms on the clay minerals are essential for the evaluation of shale gas reservoirs. In this work, combined experiments of water vapor adsorption (WVA) and nitrogen (N2) adsorption were conducted on four typical clay minerals, including montmorillonite (Mnt), illite (Ilt), chlorite (Chl), and kaolinite (Kln). Our results show that the various pore size distributions derived from the WVA and N2 adsorption data indicate that pores with a diameter smaller than 10 nm contribute 54%–82% to the total amount of water uptake. Fitting parameters obtained from five mathematical models, including the Guggenheim-Anderson-de Boer (GAB), Dent, Oswin, Freundlich, and Frenkel-Halsey-Hill (FHH), can illustrate physicochemical characteristics behind the WVA isotherm data. Compared to other models, the FHH model is more optimal to fit and predict the WVA isotherms on the four typical clay minerals. In addition, three kinetic models were utilized to evaluate the WVA kinetic behavior for the four typical clay minerals, including Pseudo-first-order (PFO), Pseudo-second-order (PSO), and Double-exponential (DE) model. Water adsorption process in the clay minerals is a two-stage process and is mainly controlled by the slow pore-diffusion process, as indicated by the best fitting results from DE model. Finally, the differences of the fitting parameters in the GAB model (the most versatile model on WVA experiments for shale rocks) and adsorption kinetics between clay minerals and shale in the WVA process were discussed, which can provide guidance for investigates of moisture distribution in the shale. Overall, the findings of this work are of great significance to determine the water distribution in the shale reservoirs and shale gas content evaluation in the actual moisture condition.

Lithofacies identification of shale reservoirs using a tree augmented Bayesian network: A case study of the lower Silurian Longmaxi formation in the changning block, South Sichuan basin, China

As important units for evaluating shale gas reservoirs, lithofacies exert obvious control on the abundance of shale organic matter and the enrichment degree of gas reservoirs. Therefore, it is of great significance to accurately identify the lithofacies of shale reservoirs relative to shale gas exploration and development. This paper takes the Longmaxi Formation shale in the Changning block, Sichuan Basin, China, as an example and uses a tree augmented Bayesian network for the quantitative classification and identification of lithofacies for the first time. First, based on thin section and scanning electron microscopy observations and X-ray diffraction, we can determine the shale lithofacies types of the Longmaxi Formation. Second, the logging response characteristics of different lithofacies were obtained by comparing conventional logging data. Finally, the tree augmented Bayesian network (TAN) was built according to the selected logging parameters and identified unknown lithofacies. The results are as follows: (1) Longmaxi Formation shale is rich in siliceous minerals. By comparing analysis of shale mineral composition and diagenetic characteristics, we divide the lithofacies into five types: siliceous rock, siliceous shale, argillaceous/siliceous mixed shale, calcareous/siliceous mixed shale and calcareous shale. (2) Based on the logging data, 6 logging curves (GR, AC, DEN, CNL, PE and RT) can sensitively indicate diagenesis and changes in mineral content. (3) The TAN model trained by logging information was used to identify 68 shale samples through the 5-fold cross validation method, with an accuracy rate of 95.58%. The results showed that the tree augmented Bayesian network not only can overcome the limitation of interdependence among well-logging properties but also represents an efficient and accurate new method for identifying shale lithofacies. This algorithm can be applied to lithofacies identification of shale reservoirs with only conventional well-logging data, which can help promote the development of lithofacies identification of unconventional oil and gas geology and provides a new method for shale gas reservoir evaluation.

Complex Resistivity Anisotropy Response Characteristics of Wufeng-Longmaxi Formation Shale in Southern Sichuan

Electrical exploration has become an important means of shale gas reservoir exploration and evaluation, and is expected to play a key role in the later stages of reservoir fracturing and development. At present, the research on the electrical response characteristics of shale gas reservoirs and their relationship with reservoir parameters is extensive and in-depth, but there is little research on their complex resistivity anisotropy characteristics and influencing factors, which restricts petrophysical modeling and reservoir parameter prediction, and reduces the reliability of shale gas exploration and reservoir evaluation by electromagnetic methods. In this paper, shale samples from the Longmaxi Formation and the Wufeng Formation of shale gas wells in southern Sichuan were collected, the complex resistivity of 34 shales in bedding direction and vertical bedding direction were measured, and the induced polarization (IP) parameters of shales were extracted by inversion. The electrical anisotropy response characteristics under different temperature and pressure conditions were analyzed, and the influencing factors and laws of complex resistivity anisotropy of shales were revealed. Combined with the test results of shale porosity and permeability, the evaluation model of resistivity, polarizability and porosity and permeability parameters was established. The research results have formed a set of testing methods and analysis techniques for electrical anisotropy of shale reservoirs, which are mainly based on complex resistivity parameter testing. It is helpful to understand the electrical anisotropy characteristics of shale gas reservoirs in southern Sichuan; this will provide the theoretical and physical basis for shale gas reservoir evaluation and fracturing monitoring by electrical exploration.

A Technique to Determine the Breakthrough Pressure of Shale Gas Reservoir by Low-Field Nuclear Magnetic Resonance

The porous and low-permeability characteristics of a shale gas reservoir determine its high gas storage efficiency, which is manifested in the extremely high breakthrough pressure of shale. Therefore, the accurate calculation of breakthrough pressure is of great significance to the study of shale gas preservation conditions. Based on a systematic analysis of a low-field NMR experiment on marine shales of the Longmaxi Formation in the Sichuan Basin, a shale gas breakthrough pressure determination technique different from conventional methods is proposed. The conventional methods have low calculation accuracy and are a tedious and time-consuming process, while low-field NMR technique is less time-consuming and of high accuracy. Firstly, the NMR T2 spectrum of shale core sample in different states is measured through low-field NMR experiment. The NMR T2 spectra of sample in water-saturated state and dry state are combined to model the mathematical relationship between shale gas breakthrough pressure and NMR T2 spectrum. It is found that the gas breakthrough pressure is power-exponentially related to the geometric mean of NMR T2 spectrum and positively related to the proportion of micropores. Accordingly, the shale gas breakthrough pressure is quickly and accurately calculated using continuous NMR logging data and then the sealing capacity of the shale caprocks is evaluated, providing basic parameters for analyzing unconventional hydrocarbon accumulation, preservation and migration. This technique has been successfully applied with actual data to evaluate the sealing capacity of shale caprock in a shale gas well in the Sichuan Basin. It can provide a good basis for the evaluation and characterization of shale oil and gas reservoirs.

Characteristics of Canister Core Desorption Gas from Unconventional Reservoirs and Applications to Improve Assessment of Hydrocarbons-in-Place

Canister core desorption has been successfully applied to coal-bed methane evaluation and exploitation as the technique eliminates the need for time-consuming down-hole fluid retrieval through flow testing. The technique has also been used for the evaluation and exploration of early-stage tight and shale gas reservoirs in recent years, although its success and applicability are poorly understood. In this study, we analyzed a comprehensive canister desorption data set on 230 core samples from nine exploration wells drilled into the Montney Formation in northeastern British Columbia part of the Western Canada Sedimentary Basin (WCSB). The purpose of the study was to illustrate the desorption characteristics of tight rocks and the relationship to reservoir properties and operational parameters. Based on the measured core properties (e.g., porosity, fluid saturation, permeability, total organic carbon (TOC) content, and adsorption isotherms) of canister samples and adjacent core samples, non-isothermal gas transport in cores was modeled to quantify the lost gas during core recovery and lost gas time at the surface. Gas volumes were measured and subsampled by canister desorption tests. The results show that the gas contents measured by on-site canister desorption only accounts for a minor (but significant) portion (about 2 to 25%) of the total gas-in-place in the Montney Formation cores, with the lower percentages being associated with samples of better reservoir qualities (e.g., higher porosity). Over 60–90% (mainly free gas) of the total gas-in-place can be lost during core recovery, and up to 10% can be lost at surface, prior to canister desorption. The measured canister desorption gas is mainly from adsorbed gas, and hence shows strong positive correlation to TOC content. The study shows that the current canister desorption test method severely underestimates in-situ gas content because it fails to correctly estimate the total lost gas content, limiting the successful application of the desorption technique. Nevertheless, the bulk properties and molecular compositions of the desorption gases are strongly correlated to those of the gases produced in the same area, exhibiting distinctive gas composition profiles throughout core desorption for different reservoir types or thermal maturity, and thus can provide invaluable information for the initial evaluation of unconventional plays. A workflow of EOS-based PVT property and compositional modeling is proposed to integrate the core desorption gas test results with core analysis data and mud gas and/or produced gas data for improved characterization of in situ reservoir fluids, and hence, better assessments of hydrocarbons-in-place and evaluations of tight and shale reservoirs.

Molecular insights into supercritical methane sorption and self-diffusion in monospecific and composite nanopores of deep shale

• Montmorillonite, kerogen and MMT-kerogen composite slit nanopores with desirable pore sizes are constructed; • GCMC and EMD simulations are conducted to study the sorption and self-diffusion behaviors of methane in various nanopores; • Pore surface roughness can impede the diffusion of gases, especially in smaller pores. Up to now, a large number of studies have utilized various representative materials to approximate the replacement of shale and investigate the gas adsorption and diffusion behavior in various shapes of nanopores by means of molecular simulations. However, the study of methane sorption and self-diffusion behavior under high temperature and pressure reservoir conditions in deep shale is not clear. In this study, we first established montmorillonite (MMT), kerogen and MMT-kerogen composite slit nanopores using representative shale components of MMT and kerogen. On this basis, we investigated the methane sorption and self-diffusion characteristics employing the grand canonical Monte Carlo (GCMC) and equilibrium molecular dynamics (EMD) simulations. The results show that the differences in the molecular composition and structure of MMT and kerogen surfaces lead to stronger adsorption performance of MMT surface than kerogen in a single nanopore for the same conditions, which results in the inhomogeneity of spatial distribution of methane molecules in the pores. While the sorption capacity of the kerogen matrix is more potent than MMT due to its larger specific surface area (SSA). The smaller pores have stronger adsorption capacity compared to the larger pores. At the same time, the methane density profiles indicate that the adsorption of the MMT and kerogen in smaller pores is less differentiated. The methane sorption energy distribution and isosteric heat of sorption also mutually corroborate the more stable methane sorption at a higher pressure and smaller pores. The self-diffusion coefficient of methane in nanopores gradually decreases with increasing pressure, with a more pronounced variation at lower pressure. Pore surface roughness will hinder the diffusion of gas, and the closer the distance is, the more noticeable the effect will be. This study sheds light on the sorption and self-diffusion phenomena and difference of gas in monospecific and composite nanopores, which provides insights into the reserve evaluation and development of the deep shale gas reservoirs, and is further expected to furnish ideas for exploring the occurrence and transport characteristics of supercritical fluids on other composite nanomaterials.

Pore accessibility by wettable fluids in overmature marine shales of China: Investigations from contrast-matching small-angle neutron scattering (CM-SANS)

The characterization of pore accessibility is essential for shale oil and gas reservoir evaluation. However, owing to the extremely low permeability and high heterogeneity of shale components, accurate nanoscale evaluation of pore accessibility remains challenging. In this study, a systematic investigation of nanoscale pore accessibility characteristics and their controlling factors was undertaken via contrast-matching small-angle neutron scattering (CM-SANS) on four overmature marine shale samples from China. In addition, a series of experiments integrating the air-liquid contact angle, spontaneous imbibition, mercury intrusion capillary pressure (MICP), and field-emission scanning electron microscopy, were conducted to determine the shale wettability and pore connectivity characteristics. A novel accessibility index was developed and utilized to analyze the accessibility of fluids with different wetting phases in nanoscale pore networks and their changes over time. The results from the CM-SANS test of Wufeng-Longmaxi shale samples indicate that higher pore volumes (pores >7 nm) were filled with toluene due to the development of organic pores and the connection between organic pores and inorganic pore systems. Meanwhile, more water-accessible pores were observed within a pore size of less than 7 nm. This result indicates that the pore volume is perhaps composed of hydrophilic pores related to clay minerals or created by the swelling of clays. Furthermore, the combination of CM-SANS on samples (before and after combustion) and MICP showed that pore accessibility to water and toluene was controlled by pore surface wettability and pore connectivity. Thus, CM-SANS is an effective means of evaluating the nanoscale pore accessibility of shale, revealing the relationship between wettability and pore connectivity, which can help better understand the migration of hydrocarbon fluids and the imbibition of fracturing fluid.

A multi-scale quadruple-continuum model for production evaluation of shale gas reservoirs considering complex gas transfer mechanisms and geomechanics

Shale gas reservoirs are uniquely characterized by extremely low values of permeability, porosity, and complex fracture network which adequately hinders gas transfer and production evaluation. At the reservoir scale, the analysis of complex gas flow and transfer mechanisms from one domain to another is still a challenge. In this regard, a fully coupled multi-scale quadruple-continuum model is proposed, where the gas transfer mechanisms across the four domains (Kerogen, inorganic matrix, natural fractures, and hydraulic fractures) are adopted and the flow terms are corrected to suit real gas and account for shale deformation considering dynamic effective stress. The complexity of modeling gas transfers from the kerogen to the inorganic matrix to fracture system (natural and hydraulic fractures) and the production well is overcome by using the Warren-Root and Vermeulen transfer terms, respectively. The current model matches field data from typical shale reservoirs and accurately predicts gas production. Numerical simulation results show that increasing the kerogen pore volume and stress sensitivity coefficient decreases cumulative gas production. Increasing domain permeability, porosity, number of natural fractures, and the width and length of natural fractures improve the flow of gas, leading to higher cumulative gas production. Moreover, crisscrossing natural fractures and larger stimulated reservoir domain (SRD) could extend the area of contact with the unstimulated reservoir domain (USRD), thus allowing more gas to flow to the production well. Overall, more gas is produced when the four domains are considered than when either of them is ignored. This study introduces a comprehensive understanding of the four domains' primary flow and transfer mechanisms. It provides a practical baseline for evaluating gas production in fractured shale reservoirs.

Shale Reservoir Heterogeneity: A Case Study of Organic-Rich Longmaxi Shale in Southern Sichuan, China

Shale reservoir heterogeneity is strong, which seriously affects shale gas reservoir evaluation and reserves estimation. The Longmaxi Formation shale of the Luzhou block in southern Sichuan was taken as an example to characterize the pore distribution of shale over the full scale using micro-computed tomography (CT), focusing on ion beam scanning electron microscopy (FIB-SEM) and small-angle neutron scattering (SANS); further, the heterogeneity of the shale pore distribution over the full scale was explored quantitatively within different scales. The results show that shale micropores are dominated by microfractures that are mainly developed along the bedding direction and associated with organic matter, contributing 1.24% of porosity. Shale nanopores are more developed, contributing 3.57–4.72% porosity and have strong heterogeneity locally at the microscale, but the pore distribution characteristics show lateral homogeneity and vertical heterogeneity at the macroscale. In the same layer, the porosity difference is only 0.1% for the sheet samples with 2 cm adjacent to each other. Therefore, in shale core experiments in which parallel samples are needed for comparison, parallel samples should be in the same bedding position. This paper explores the extent of heterogeneity over the full scale of pore distribution from macro to micro, which has important significance for accurately characterizing the pore distribution of shale and further carrying out reservoir evaluation and estimation of reserves.

Data-driven machine learning approach to predict mineralogy of organic-rich shales: An example from Qusaiba Shale, Rub’ al Khali Basin, Saudi Arabia

The Qusaiba Shale is a proven source rock for the Palaeozoic petroleum system of the middle east and it is targeted as a potential source of unconventional shale gas potential reservoirs in Saudi Arabia and recently considered a possible source of unconventional gas. Mineralogy of shale plays a key role in the successful design and performing the hydraulic fracturing operations and in turn evaluating the production potential. There is limited research available in the literature on the application of artificial intelligence for mineralogical prediction, which motivate us to perform this research on the Qusaiba Shale. The study aims to predict the Qusaiba Shale mineralogy, specifically clay and quartz minerals using readily available conventional logs, where both minerals are the major constituents of shale and help in assessing the brittle and ductile zones within the shale formation. Three lithofacies were defined in the Qusaiba Shale based on different geological and sedimentary features of core samples, and they have different ranges of quartz and clay content. Predictive models were developed for two utmost important minerals present in Qusaiba Shale formation including clay and quartz using artificial intelligence techniques. An adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANN) were employed to precisely predict the two major minerals contents in Qusaiba Shale formation. All four models were found to have good accuracy. ANN-based models exhibited minimal errors with AAPE and RMSE of 2.53 and 1.45 for quartz and 3.43 and 2.01 for unseen data points for clay prediction models respectively. ANFIS-based prediction models presenting the AAPE and RMSE 2.67 and 1.83 for predicted quartz values and 3.59 and 1.89 for the clay content respectively. The applied artificial intelligence predictive model for major minerals in Qusaiba Shale i.e., clay and quartz would be a viable and useful approach to achieve valuable information about minerals content in shale for prospective evaluation of shale gas reservoirs. The results of this work would be useful in prospect evaluation and optimizing the production from unconventional shale gas reservoirs in Saudi Arabia. Moreover, the approach used may provide insights into replacing traditional mineralogy determination methods to save cost and resources in the absence of cores and mineralogy logs in the unconventional Qusaiba Shale resource. Furthermore, applying the same artificial intelligence approach and steps could be used for the field development of other shale gas and oil fields worldwide.

Quantitative characterization of pore network and influencing factors of methane adsorption capacity of transitional shale from the southern North China Basin

Quantitative characterization of pore structure and analysis of influencing factors of methane adsorption are important segments in shale gas reservoir and resources evaluation and have not been systematically carried out in marine–continental shale series. A series of integrated methods, including total organic carbon (TOC) contents, Rock-Eval pyrolysis, mineral composition analysis, pore structure measurement, high-pressure CH4 adsorption analysis and FE-SEM observation, were conducted on 12 transitional shale samples of well WBC-1 in the southern North China Basin (SNCB). The results indicate that TOC contents of the transitional shales range from 1.03 to 8.06% with an average of 2.39%. The transitional shale consists chiefly of quartz, white mica and clay minerals. Interparticle pore, intraparticle pore, dissolution pore and microfracture were observed in the FE-SEM images. The specific surface area (SSA) of BET for the samples ranges from 3.3612 to 12.1217 m2/g (average: 6.9320 m2/g), whereas the DR SSA for the samples ranges from 12.9844 to 35.4267 m2/g (average: 19.67 m2/g). The Langmuir volume (VL) ranges from 2.05 to 4.75 cm3/g (average = 2.43 cm3/g). There is unobvious correction between BET and DR SSA with TOC contents, which means inorganic pores are the main component of pore space in the transitional shale from the SNCB. The relationship of SSA and pore volume shows that micropore has a greater impact on the CH4 adsorption capacity than mesopore–macropore in the transitional shale. Different from shales in other petroliferous basin, clay minerals are the primary factor affecting adsorption capacity of CH4 for transitional shale in this study. The pore structure of the transitional shale for this study is characterized by higher fractal dimension and more heterogeneous pore structure compared to shale in other petroliferous basin. This study provides an example and new revelation for the influencing factors of pore structure and methane adsorption capacity of marine–continental transitional shale.

Optimization of key parameters for porosity measurement of shale gas reservoirs

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.

Shale gas enrichment model and exploration implications in the mountainous complex structural area along the southwestern margin of the Sichuan Basin: A new shale gas area

Marine shale gas in the southern Sichuan Basin is the most successful area of shale gas exploration and development in China. In order to open up new shale gas fields and search for new shale gas reserves and production replacement blocks, it is necessary to continuously establish and complete the standards on shale gas reservoir evaluation and area selection under different structural settings. The early exploration practice shows that shale in the mountainous complex structural area along the southwestern margin of the Sichuan Basin varies greatly in the gas bearing property, so systematical analysis and study on the shale gas enrichment mechanisms in this area is of great significance to searching for new shale gas exploration areas. Based on drilling data of 5 wells in the mountainous complex structural area along the southwestern margin of the Sichuan Basin, the main factors controlling the shale gas bearing property and the shale gas enrichment model were discussed based on the systematical experiments and analysis of the outcrops, cores and cuttings of Longmaxi Formation shale from the aspects of organic geochemistry, physical property, gas content, hydrocarbon generation history and pore evolution history, so as to lay a solid geological basis for the birth of a new shale gas area. And the following research results were obtained. First, the shale of the first submember of first Member of Longmaxi Formation (S1l11) in the mountainous complex structural area along the southwestern margin of the Sichuan Basin has an average TOC of 3.02%–4.97% and Ro of 2.38%–3.37%, and the average total gas content in local enrichment zones is up to 4.62 m3/t, so it is classified as quality shale. Second, the detailed studies on hydrocarbon generation history indicate that the shale has the characteristics of “low thermal evolution rate and low maturity”. It is characterized by late hydrocarbon generation, low thermal evolution rate, low current maturity and short late diffusion time, which are favorable for shale gas enrichment. Third, the pore evolution history reveals that shale pore evolution can be divided into six stages, i.e., sharp pore reduction, pore reduction, organic pore formation, pore preservation, organic pore dissipation and karstification, and organic pore and TOC are the most direct control factors of shale gas content. Fourth, favorable shelf facies belt is conducive to the formation of large-scale reservoir space and effective pores, and diversities of preservation conditions under different structural styles and at different structural positions control different pore evolution stages. The shale gas in the mountainous complex structural area is characterized by horizontal zoning and differential enrichment. “Low thermal evolution rate and low maturity” and “slow structural uplifting” are beneficial to the long-term enrichment and preservation of shale gas. In conclusion, the mountainous complex structural area along the southwestern margin of the Sichuan Basin has a shale gas enrichment model of “sedimentation controlling source rocks, diagenesis controlling reservoirs and structure controlling preservation”. This research result provides idea and reference for searching for new shale gas areas and fields.

A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China

Shale gas reservoir evaluation and production optimization both require geological models. However, currently, shale gas modeling remains relatively conventional and does not reflect the unique characteristics of shale gas reservoirs. Based on a case study of the Fuling shale gas reservoir in China, an integrated geological modeling workflow for shale gas reservoirs is proposed to facilitate its popularization and application and well improved quality and comparability. This workflow involves four types of models: a structure-stratigraphic model, reservoir (matrix) parameter model, natural fracture (NF) model, and hydraulic fracture (HF) model. The modeling strategies used for the four types of models vary due to the uniqueness of shale gas reservoirs. A horizontal-well lithofacies sublayer calibration-based method is employed to build the structure-stratigraphic model. The key to building the reservoir parameter model lies in the joint characterization of shale gas “sweet spots.” The NF models are built at various scales using various methods. Based on the NF models, the HF models are built by extended simulation and microseismic inversion. In the entire workflow, various types of models are built in a certain sequence and mutually constrain one another. In addition, the workflow contains and effectively integrates multisource data. Moreover, the workflow involves multiple model integration processes, which is the key to model quality. The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. The workflow allows the complex process of geological modeling of shale gas reservoirs to be more systematic. It is of great significance for a dynamic analysis of reservoir development, from individual wells to the entire gas field, and for optimizing both development schemes and production systems.