Gas Development Research Articles

Research on Nondestructive Testing Technology for Drilling Risers Based on Magnetic Memory and Deep Learning

Drilling risers play a crucial role in deepwater oil and gas development, and any compromise in their integrity can severely hinder the progress of drilling operations. In light of this, efficient and accurate nondestructive testing of drilling risers is paramount. However, existing inspection equipment falls short in both efficiency and accuracy, posing challenges to the sustainability of deepwater oil and gas exploration and development. To effectively assess the damage conditions of deepwater drilling risers, this study developed an inspection robot based on metal magnetic memory and researched intelligent defect recognition methods using computer vision. The robot can perform in situ inspections on drilling risers and has been successfully deployed for field application on a deepwater drilling platform. The application results demonstrate that this detection robot offers significant advantages regarding high reliability and detection efficiency. Utilizing data collected on-site, we constructed a dataset containing 1100 images that cover five typical types of defects in drilling risers, including pitting, groove corrosion, and wear. Based on this dataset, we proposed and trained a novel image classification model, SK-ConvNeXt-KAN. By deeply optimizing the ConvNeXt convolutional network incorporating the introduced SK attention module and replacing traditional linear classification layers with the KAN module, this model significantly enhanced its feature extraction capabilities and efficiency in handling complex nonlinear problems. Experimental results show that this model achieved an accuracy rate of 95.4% in identifying defects in drilling risers, which is significantly better than traditional methods. This achievement has dramatically improved the efficiency and accuracy of deepwater drilling riser inspections, providing robust technical support for deepwater oil and gas exploration and development sustainability.

Characteristics and Control Factors of a High-Quality Deeply Buried Calcareous Sandstone Reservoir, the Fourth Member of the Upper Xujiahe Formation in the Western Sichuan Basin, China

A special type of sandstone in which carbonate rock fragments (CRFs) dominate the composition developed in the Upper Triassic Xujiahe Formation’s fourth member (Xu4) in the western Sichuan Basin, known as calcareous sandstone. Calcareous sandstones are widely distributed in the western Sichuan and is the main production target of tight sandstone gas in the Sichuan Basin. In this study, thin sections, porosity–permeability testing, scanning electron microscopy, and X-ray diffraction are applied to examine the characteristics and control factors for high-quality reservoirs in the calcareous sandstones, with a view to providing guidance for natural gas exploration and development in calcareous sandstones. The results show that the calcareous sandstone belongs to litharenite, with an average framework grain composition of 30% quartz, 1% feldspar, and 69% rock fragments, while the Xu4 sandstone has a high quartz content (average content of 71%). Primary intergranular pores are the main storage space, and the reservoir quality is quite poor. Under the influence of different parent rock properties of sandstones, there are obvious differences in the composition of framework grains between the calcareous sandstone and the ordinary Xu4 sandstone, which in turn affects the reservoir storage space, diagenesis, and reservoir quality. High-energy depositional conditions, low content of late cements, and the development of fractures are the main controlling factors for the formation of high-quality reservoirs in Xu 4 calcareous sandstones.

A new method of rock type identification based on transformer by utilizing acoustic emission.

The characterization and analysis of rock types based on acoustic emission (AE) signals have long been focal points in earth science research. However, traditional analysis methods struggle to handle the influx of big data. While signal processing methods combined with deep learning have found widespread use in various process analyses and state identification, effective feature extraction using progressive fusion technology still faces challenges in the field of intelligent rock type identification. To address this issue, our study proposes a novel framework for rock type identification based on AE and introduces a new signal identification model called 3CTNet. This model integrates convolutional neural networks (CNNs) and Transformer encoder, intelligently identifying AE of different rock fractures by establishing dependencies between adjacent positions within the data and gradually extracting advanced features. Furthermore, we experimentally compare five oversampling methods, ultimately selecting the adaptive synthetic sampling method (ADASYN) to balance the dataset and enhance the model's robustness and generalization ability. Comparison of the internal structure of our model with a series of time series processing models demonstrates the effectiveness of the proposed model structure. Experimental results showcase the high identification accuracy of the intelligent rock type identification model based on 3CTNet, with an overall identification accuracy reaching 98.780%. Our proposed method lays a solid foundation for the efficient and accurate identification of formation rock types in geological exploration and oil and gas development endeavors.

Predicting the Gas Storage Capacity in Shale Formations Using the Extreme Gradient Boosting Decision Trees Method

Accurate shale gas reserves estimation is essential for development. Existing machine learning (ML) models for predicting gas isothermal adsorption are limited by small datasets and lack verified generalization. We constructed an “original dataset” containing 2112 data points from 11 measurements on samples from 8 formations in 3 countries to develop ML‐based prediction models. Similar to previous ML models, total organic matter, pressure, and temperature are characterized as the three most significant features using the mean impurity method. In contrast to previous ML models, the study reveals that these three features are inadequate to be used to make reasonable predictions for the datasets from the measurements different from those used to train the models. Instead, the extreme gradient boosting decision trees (XGBoost) model with two more features (specific surface area and moisture) exhibits good robustness, generalization, and precision in the prediction of gas isothermal adsorption. Overall, An XGBoost model with optimal input features is developed in this work, which exhibits both good performance in gas adsorption prediction and good potential for the estimation of gas storage in shale gas development.

Investigation into the Variation Law of Network Fracture Conductivity in Unconventional Oil and Gas Reservoirs

The network fracturing technique is a key technology for increasing effective reservoir volume and enhancing production in shale oil and gas. The fracture network’s conductivity is one of the crucial factors affecting the efficient development of shale gas. To evaluate the variation patterns and influencing factors of the conductivity of network fractures, this study employed a proppant conductivity evaluation system and an equivalent theory testing method. It investigated the conductivity of propped and self-propped fractures under different angles and numbers of fractures. Experimental results showed that fractures with proppant support had higher conductivity than unsupported fractures. Smaller angles between secondary and main fractures resulted in greater conductivity. The conductivity of multi-fracture structures increased with the number of fractures. Under low-closure pressure conditions, self-propped fractures exhibited significantly higher conductivity than propped fractures, but this trend reversed under high closure pressure. This experimental research provides guidance for constructing network fractures with high conductivity in unconventional oil and gas reservoir fracturing.

Fractured perceptions: Unconventional oil and gas development and the social construction of perceptions of risk in South Africa

To address energy shortages, the South African government includes the development and extraction of local natural gas as part of its future energy plan. Insights into risk perception are crucial for determining realistic and likely risks relevant to future energy developments in the face of the country's future energy planning. Studies on the social construction of the risk perceptions of unconventional oil and gas (UOG) development are lacking since risk perceptions of UOG development in South Africa are not underpinned by tangible, lived experiences. This study, therefore, offers novel insights into the social construction of risk perceptions. We identified the risk objects, objects at risk, and factors influencing risk perceptions, and found that UOG development risk perceptions in South Africa are socially constructed through group membership and participation. The perceived rivalry between opposition and proposition groups prompts stakeholders to deliberately formulate ideas, opinions, and viewpoints to counter those of oppositional groups. We propose a risk communication strategy that considers the media's influence on stakeholders’ risk perceptions, aims to understand the different stakeholder groups’ views, intentions and expected behaviour, and tailors communication that acknowledges groups’ different goals and intentions. The proposed strategy considers the diverging opinions of the opposing groups in a collaborative effort to build trust in and between groups.

Prediction of deep low permeability sandstone seismic reservoir based on CBAM-CNN

The prediction of sand body is a key focus in evaluating reservoir distribution, playing a crucial role in oil and gas exploration and development. To clarify the development characteristics of the sand body in the Huangyan structural belt of the Xihu Sag and effectively identify the hidden channel, a new approach is proposed. This approach incorporates a Convolutional Block Attention Module (CBAM) into a Convolutional Neural Network (CNN). Well logging and seismic data were used to predict the distribution of sand body in the lower section of the Huagang Formation (H12). Firstly, based on known sand-stratum ratio data and well-side seismic data, the seismic attributes that are sensitive to the reservoir response are preferred through correlation analysis, which are used to construct a Polynomial Linear Regression (PLR) model to obtain the preliminary sand distribution prediction results. Secondly, the grid is divided according to this result. Then, three sample selection methods, namely proportional, fixed-range, and random, are used to construct three sample sets in conjunction with the geologic model guide. Finally, CBAM-CNN, CNN, Random Forest (RF), Support Vector Machines (SVM), and Backpropagation Neural Network (BPNN) are utilized for sand body prediction. The results indicate that when using the same model, the sample set selected by the fixed-range selection method yielded the best prediction outcome. When using the same sample set, the CBAM-CNN model outperformed the others. Among various strategies, training the CBAM-CNN model with the sample set derived from the fixed-range selection method led to the highest test set R2 of 0.913. The results of the sand body distribution indicate that fine river channels are more continuous, and reservoir boundaries are clearer, significantly outperforming other schemes. This outcome can serve as a guide for further reservoir delineation.

Reconstruction of large-scale anisotropic 3D digital rocks from 2D shale images using generative adversarial network

Digital rock technology has played a significant role in unconventional oil and gas exploration and development. Current techniques face challenges such as high cost or low efficiency when reconstructing 3D pore structures at the nanoscale, which limit the study of rock physical properties in reservoirs. To address these issues, this work proposes an efficient generative adversarial network workflow for generating large-scale anisotropic 3D digital rocks from 2D images. Instead of relying on 3D data, the model is trained using only 2D images. During training, rock images taken from various angles can be utilized to construct anisotropic 3D digital rocks. Moreover, a novel method for generating large-scale 3D data is devised, where the input random noise is divided with overlap to generate small-scale digital rocks and concatenated into a larger-scale 3D digital rock. The similarity between the 3D reconstructed data and the training images was assessed separately, as well as the pore structure of the 3D reconstructed data, and the feasibility of the proposed method was verified using the simulation of absolute permeability. The digital rock modeling process presented in this study enables rapid and accurate 2D-to-3D large-scale digital rock modeling, providing an effective representation of the anisotropy present in shale oil reservoirs.

AC breakdown and decomposition products detection characteristics of eco-friendly insulating medium in gas insulated switchgear

Gas Insulated Switchgear (GIS) was a crucial electrical equipment that provides the safety and security of power systems, and finding the eco-friendly alternatives of sulphur hexafluoride (SF6) as insulating medium in GIS has been an urgent demand in past decades. However, few studies reported the specific dielectric strength under various electrodes and partial discharge (PD) decomposition products detection of applying the eco-friendly gas in GIS. In this paper, the insulation properties among C4F7N/CO2 mixtures, dry air and CO2 were explored under the reduced-scale gas-insulated experimental device. The relationship between AC breakdown voltage and gas pressure was gained under the different electrodes and gap distances, and 0.6 MPa 7% C4F7N/93% CO2, 0.9 MPa dry air, 0.9 MPa CO2 all possess the capacity to be the insulating medium in eco-friendly gas insulated switchgear. Furthermore, the partial discharge experimental was also carried out to realize the decomposition products detection of dry air, which designs three common defect types including metal protrusion defects, air gap defects, and metal contamination defects. The decomposition products detection result shows that the contains of CO2, CO, and NO2 linearly increase with the increasing applied voltages and times, and the partial discharge defects are distinguished according to the ratios of c(CO2 + CO)/c(NO2) and c(CO2)/c(CO). The results can provide the basis for the further development of eco-friendly gas insulated switchgear.

Exploring the prospects of deep natural gas resources from the geochemical parameters of the Shahejie Formation source rocks in the Banqiao depression

Deep natural gas is an important field and direction for oil and gas exploration and development in the Banqiao depression. The geochemical characteristics of the Paleogene Shahejie Formation source rocks in the Banqiao Sag were investigated based on pyrolysis, Total Organic Carbon (TOC), chloroform bitumen A, vitrinite reflectance, saturated hydrocarbon gas chromatography–mass spectrometry, and maceral determination. The results showed that the Es3 source rocks of the Paleogene Shahejie Formation were generally of better quality than the Es1 source rocks. Regarding the Es1 source rocks, the abundance of organic matter was variable, with mixed types and low maturity. The source rocks were formed in a saline-water reductive environment. Regarding the Es3 source rocks, the abundance of organic matter was relatively high, meaning that they were of medium–high quality, with mixed types of, yet highly mature, organic matter. The hydrocarbon generation environment was oxidative, and the source rocks were mainly deposited in fresh water with localized salinization. The main hydrocarbon-generating components of organic matter in the Shahejie Formation were amorphous humic components formed by intensive microbial modification of lower planktonic algae and terrestrial higher plants. Aquatic organisms were the main sources of organic matter, with localized mixing of higher-plant organic matter. The organic matter derived from these higher plant debris sources provided beneficial conditions for the generation of natural gas. At present, the Shasan source rock is at the peak of hydrocarbon generation. Under deep conditions, the maturity of organic matter increases, and organic matter rich in terrestrial higher plants can make a significant contribution to the generation of natural gas, especially shale gas.

End-Member Mixing Model for Methane Carbon Isotope Fractionation During Shale Gas Desorption and Its Application.

Unlike conventional natural gas reservoirs, shale gas development involves systematic changes in methane carbon isotopes that cannot be effectively described by existing isotope fractionation models and mechanisms. Therefore, based on fundamental theories such as Rayleigh fractionation, mass transfer flow, and mass conservation, this study established isotopic fractionation equations for methane in adsorbed and free gas. By considering adsorbed and free gases as two end-members and using an isotope mixing model, a fractionation model for methane carbon isotopes during shale gas desorption was constructed. This model quantifies the isotopic fractionation effects during shale gas desorption and elucidates the mechanism of methane carbon isotope fractionation. Using on-site desorbed gas content and isotope data, parameter fitting and model calculations were conducted to characterize methane carbon isotope variations throughout the process of shale core field desorption. The results show a pattern of "initially negative and then turning positive," consistent with those of physical simulation experiments. It was clarified that differences in mixing the two end-members and isotopic fractionation play key roles in the variation of methane carbon isotopic composition in shale gas. By applying the methane carbon isotope fractionation model, the contribution of adsorbed gas during shale gas production was explored. It was found that in the early stage of development, the adsorbed gas in Well JY 1 was negligible. After nearly seven years of development, the contribution of adsorbed gas in the later stage has only reached nearly 15%, indicating that the production contribution of adsorbed gas is still less than 0.3 million cubic feet per day. The open flow of Well JY 6-2 is more conducive to the production of adsorbed gas, but the production capacity is still mainly contributed by free gas, indicating that the shale gas production capacity in the later stage in the Jiaoshiba gas field is still primarily dominated by free gas.

New Evidences of Fluid Inclusions from Wufeng Formation Reveal Shale Gas Accumulation and Leakage Histories in Northern Guizhou, Southwestern China

Abstract Shale gas accumulation and leakage histories are significant for evaluating the prospects of hydrocarbon exploration. The Wufeng Formation in northern Guizhou is a potential target for shale gas exploration and development. This work selected a typical Well YH1 to conduct detailed fluid inclusion analyses in the Wufeng Formation. We integrated the inclusion results with systematic core description, thin-section microscopic observation, laser Raman spectroscopy, microscopic temperature measurement, and burial–thermal history to reveal shale gas accumulation and leakage histories in northern Guizhou. The results show that the source rocks of the Wufeng Formation occurred in oil generation since the Permian and entered the stage of natural gas generation at the end of the Late Triassic. During the Early Jurassic and Early Cretaceous, shale gas accumulated in the Wufeng Formation reservoirs, and the stratigraphical pressure coefficient ranged from 1.47 to 1.97. Under the influence of the Yanshan orogeny, northern Guizhou experienced a rapid uplift and exhumation since the end of the Early Cretaceous. Under the influence of this tectonic, the stratigraphical pressure plummeted to the normal level, adversely impacting the accumulated shale gas in reservoirs and resulting in leakage events since the end of the Early Cretaceous. The reservoirs were further destroyed and adjusted, and the gas continued to leak because of a long-term and large-scale uplift and exhumation during the Himalayan orogeny. This work clarified that shale gas accumulation and leakage histories are significant for evaluating petroleum exploration.

Prediction of Structural Fracture Distribution and Analysis of Controlling Factors in a Passive Continental Margin Basin—An Example of a Clastic Reservoir in Basin A, South America

Structural fracture distribution is essential in oil and gas transportation and development in passive continental margin basins. In this paper, taking as an example the clastic reservoirs in the A-Basin, a passive continental margin in northeastern South America, the paleotectonic stress field of the Late Cretaceous Maastrichtian formation in Basin A was numerically simulated by finite element technique through the integrated interpretation of seismic total data, logging data and core data, and the distribution of tectonic fractures was later predicted based on rock fracture criterion. The results of the study show that: (1) The distribution of tectonic stress and fractures during the Late Cretaceous Maastrichtian formation of Basin A is affected by the fracture zone, mechanical properties of rocks and tectonic stress, regions with extensive fracture development are susceptible to stress concentrations, resulting in significant stress gradients. (2) The development of structural fractures in the study area was predicted using the Griffiths criterion, and the tensile rupture coefficient T was introduced to quantitatively characterise the intensity of fracture development, with larger values reflecting a higher degree of fracture development. The well-developed and relatively well-developed fractures are mainly located in the fracture zones and the interior of submarine fans. (3) Fracture zones and sedimentary phases mainly control structural fractures in Basin A; within 5 km outside the fracture zones, the development of fractures is controlled by the fracture zones, beyond which the regional tectonic stress field controls them; inside the sedimentary fan, the development of fractures is controlled by the sedimentary subphase, which decreases in the order of the upper fan, the middle fan, and the lower fan; inside the subphase, they are controlled by the regional tectonic stress field, and the fractures show the increasing trend in the direction of NW-NE.

Proximity of public K-12 schools to oil and gas development in the U.S.: Implications for environmental justice and children’s health

Proximity of public K-12 schools to oil and gas development in the U.S.: Implications for environmental justice and children’s health

Multidimensional Impacts of Oil and Gas Development on Mental Health: Methods & Results from a North American Preconception Cohort Study

Multidimensional Impacts of Oil and Gas Development on Mental Health: Methods & Results from a North American Preconception Cohort Study

Associations between Residential Proximity to Oil and Gas Development and Hypertensive Disorders of Pregnancy in a North American Preconception Cohort

Associations between Residential Proximity to Oil and Gas Development and Hypertensive Disorders of Pregnancy in a North American Preconception Cohort

A review of spatial-temporal data sources for estimating population-level exposures to oil and gas development in the United States

A review of spatial-temporal data sources for estimating population-level exposures to oil and gas development in the United States

Research Progress and Suggestions on Natural Gas Industry Technology Revolution in the Context of Energy Revolution

The energy revolution is an important driving force for the progress of productivity and civilization in human society. As a big country in global energy consumption and carbon emission, promoting the energy revolution is a strategic choice to ensure the sustainable development of China's energy industry, which is in line with China's national conditions of the construction of modern energy system. Based on the strategic background of the energy revolution, this paper combines China's natural gas production capacity and consumption demand in the context of national conditions, and from the perspective of technological revolution, we have sorted out the research results of relevant scholars on the natural gas industry and the technological development of the whole industry chain of “production, supply, storage and marketing”, and discussed the technological development of China's natural gas industry in the context of the energy revolution. The results of the study show that: (1) the innovative technology of natural gas industry is diversified, low-carbon and green development, but from the dimension of safety, stability and economy, the performance is relatively weak. (2) The overall synergistic development of the whole industrial chain technology is uneven, the gap between supply and demand is increasing, and the degree of information and intelligence is low. And then for the development of China's natural gas industry technology puts forward proposals: (1) to promote innovative natural gas technology breakthroughs, integration of new areas of technology, to achieve the dual objectives of low-carbon economic development and environmental protection; (2) to increase natural gas exploration and development efforts, breakthroughs in the integration of the digital transformation of traditional exploration technology, and continue to support the increase in storage and production; (3) to accelerate the upgrading of natural gas supply and demand, and the establishment of a synergistic, intelligent, diversified pipeline network system. (4) Boost the construction of gas storage system, pay attention to the standardized gas storage management system, and play the role of valley cutting and peak leveling; (5) Build a new comprehensive energy service system, and build a multi-species, multi-link intelligent technology integration to create a new service system.

Strontium isotopes in the atmosphere, geosphere and hydrosphere: Developing a systematic “fingerprinting” framework of rocks and water in sedimentary basins in eastern Australia

Understanding the connection between aquifers, aquitards, and groundwater-dependant ecosystems remains a key challenge when developing a conceptual hydrogeological model. The aim of this study was to develop a systematic strontium isotope (87Sr/86Sr) fingerprinting framework of rocks and water within the sedimentary Surat and Clarence-Moreton basins (SCM basins) in eastern Australia – an area of extensive coal seam gas development and high potential for aquifer and groundwater-surface water connectivity. To do this, new groundwater samples (n = 298) were collected, analyzed and integrated with published data (n = 154) from the basins' major sedimentary, volcanic and alluvial aquifers, including the major coal seam gas target, the Walloon Coal Measures. Samples were also analyzed from rainfall (n = 2) and surface water (n = 40). In addition, rock core samples (n = 39) from exploration and stratigraphic wells were analyzed to determine the range of Sr isotope composition from host rocks. The analyses of cores demonstrate a distinct and systematic contrast in 87Sr/86Sr between different hydrogeological units. This confirms that all major hydrogeological units have a narrow range with unique 87Sr/86Sr population characteristics that are useful for guiding conceptual model development. Comparison with selected hydrochemical and groundwater age tracers (14C and 36Cl) suggests only limited changes of 87Sr/86Sr from recharge beds to the deeper parts of the basins or with a decrease in natural 14C and 36Cl tracer content along flow paths. Stream sampling during baseflow conditions confirms that 87Sr/86Sr in surface waters are similar to those of the underlying bedrock formations. We demonstrated that 87Sr/86Sr analyses of rocks and water provide a powerful hydrostratigraphic and chemostratigraphic fingerprinting framework in the SCM basins, enabling reliable assessments of plausible aquifer and groundwater-surface water interconnectivity pathways. Applied in other complex multi-aquifer sedimentary basins in Australia, and globally, a similar approach can help to constrain conceptual hydrogeological models and facilitate improved water resource management.

Analysis of Rock Mechanical Characteristics and Establishment of an Evaluation System for Coal Measures in the Longtan Formation, Guizhou Province.

The mechanical properties of coal measure rocks and their evaluation significantly impact the process and efficacy of coal measure exploration and development. This study focuses on the Guizhou Longtan Formation coal measure. The mechanical and fracturing characteristics of coal measure rock samples are analyzed via well coring, geophysical logging, and indoor experiments. Additionally, predictive models for rock mechanical parameters are developed, and an evaluation system for the Longtan Formation coal measure rock mass is established. The findings are as follows: (1) Coal measure rocks in Guizhou's Longtan Formation exhibit a relatively low elastic modulus and tensile strength, but a substantial variation in compressive strength. The triaxial compressive strength, elastic modulus, and residual strength increase nonlinearly with increasing confining pressure. As the confining pressure increases, the failure mode of the mudstone and siltstone transitions from primarily splitting failure to shearing failure. (2) Strong correlations are calculated between logging parameters and rock mechanical parameters and are used to construct three regression prediction models, yielding an average prediction accuracy of approximately 85% for rock mechanical properties. (3) Considering the rock mechanical properties, rock mass structure and stratigraphic characteristics, and the occurrence environment related to the characteristics of rock mass affecting coal measure gas development, eight evaluation indices are selected. The analytic hierarchy process-entropy weighting method is used to determine the weights of the comprehensive evaluation indices, and a coal measure rock mass evaluation system is established by utilizing gray clustering analysis. The evaluation results categorize the mudstone group (mudstone and silty mudstone) as Classes III-IV, the fine sandstone group as Classes I and II, and the siltstone group (muddy siltstone and siltstone) as Classes II and III. A comparative analysis with fuzzy comprehensive evaluation results and extenics theory evaluation results demonstrated a high level of consistency. These findings benefit coal measure rock mechanics classification and quantitative research on rock mechanics properties, providing a solid foundation for efficient coal measure gas exploration and development.