In the wave of global energy transition，the innovation of energy storage technology is extremely important for ensuring stable energy supply and sustainable development. Deep underground salt caverns have become the preferred storage space for energy resources such as oil，natural gas，and hydrogen，due to their characteristic stability and containment，with extensive applications across the world and significant application results. Compared to the oil blanket method for cavern construction，cavern construction with nitrogen dissolution inhibition is safer and more efficient，environment friendly and cost effective for salt cavern energy storage facilities. This paper focuses on the cavern construction technology with nitrogen dissolution inhibition for salt cavern energy storage and presents a comparative analysis of cavern construction techniques with oil and gas blanket for dissolution inhibition. The cavern construction with nitrogen dissolution inhibition is clarified，including the wellhead workflow modification，on-site nitrogen injection process，and gas-liquid interface monitoring and control technique. It also lists and investigates application cases in both China and other countries. Based on a thorough literature review，this paper concludes the important effects of cavern construction with nitrogen dissolution inhibition on improving the construction efficiency of gas storage，reducing costs，and protecting environment. Moreover，the future development trend of this technology is explored.

In the background of China's goals of "Dual Carbon"，hydrogen，as clean energy，is expected to be widely used；however，it leads to large carbon emissions in the production process. Hydrocarbon Steam Reforming （HSR） is a common pro- cess for hydrogen production in refineries，in which accurate carbon accounting is hard to perform，due to the high fluctuation of feed- stock and low frequency of monitoring of key carbon emissions data. In this paper，the hydrogen production process of a refinery was taken as an example，and the HSR model was built by Aspen Plus to analyze the impact of different process parameters on carbon emis- sions in order to address the lack of accurate carbon measurements. Due to the large variation of some important parameters in the actu- al production process，it is hard for a steady model to produce sufficiently accurate simulation data . This performed experiment inter- connected MATLAB with Aspen Plus and changed model input parameters in accordance with the actual production data to achieve the dynamic simulation of the production process. The experimental results verified that the proposed model can well simulate the actual hydrogen production process and thus，provide data support for accurate carbon accounting.

Most of the oil and gas fields in China are located in remote areas with low ambient temperature throughout the year. It is necessary to heat the wellhead to prevent freezing. Micro catalytic burners can be used in many heating scenarios. However，methane alone is difficult to stably catalytically self-ignite at room temperature. By using China's abundant renewable energy such as wind power and photovoltaic power to produce green hydrogen and mix it with methane on precious metal Pt，catalytic self-ignition at room temperature can be achieved. Research on catalytic combustion of green hydrogen and methane mixed fuel is expected to play an important role in developing new techniques for wellhead anti-freezing and accelerate "low-carbonization" of energy. The reaction files of the catalytic reaction mechanism of hydrogen and methane mixed fuel on the surface of Pt catalyst are studied and imported into Fluent 2021R1 to build a three dimensional numerical computation model for the catalytic combustion of hydrogen and methane mixed fuel in micro-channels and explore the effects of the mixing ratio of hydrogen-methane and the synchronous and asynchronous supply of hydrogen and methane on the ignition of catalytic combustion. It is found that a low proportion of hydrogen leads to the deactivation of the catalyst，and a high proportion of hydrogen can trigger catalytic spontaneous combustion at room temperature. The synchronous supply mode is associated with a higher upper limit of the hydrogen proportion for catalyst deactivation and a smaller lower limit of the hydrogen proportion for catalytic spontaneous combustion. The simulation results show that the synchronous supply of hydrogen and methane，an inlet velocity of 1.0 m/s，a hydrogen and methane concentration ratio of 1∶1，and a micro-channel diameter of 1.5 mm are favorable for the catalytic self-ignition of hydrogen and methane mixed fuel. The performed numerical simulation reveals the catalytic self-ignition characteristics of green hydrogen and methane mixed fuel at room temperature and the evolution law of the ignition process，which lays a foundation for the application of such heating processes in oil and gas field production.

To mitigate climate change by reducing CO₂ emission，carbon capture，utilization，and storage （CCUS） technologies have garnered significant attention. However，the required large scale investment and inflexibility of CCUS projects have greatly hindered their widespread applications. In this context，systematic source-sink matching has emerged as a key research focus，as scientific and efficient matching can optimize pipeline network design and reduce the overall costs of CCUS implementation. To this end，this study proposes a CCUS pipeline network layout optimization method using Density-Based Spatial Clustering of Applications with Noise （DBSCAN），offering a solution for CCUS pipeline network design. Firstly，the DBSCAN clustering is employed to cluster emission sources and storage sinks. Subsequently，a CCUS source-sink matching model is developed based on the minimum spanning tree method after comprehensively considering source-sink characteristics and cost components across operational phases to generate theoretical CCUS matching schemes. Finally，to address pipeline redundancy caused by multi-sources to one-sink configurations，an improved saving algorithm is applied to optimize the CCUS source-sink matching scheme. A hypothetical planning region is presented for testing of the proposed method，which demonstrates that the model does not only reduce deployment costs but also significantly shortens transportation distances. Compared with traditional methods，the total deployment costs decrease from 130 billion CNY to 98 billion CNY，by a reduction of approximately 24.6%，while the transportation distance is reduced from 4 075 km to 1 008 km，marking a decrease of 75.3%. These findings validate the adaptability and economic efficiency of the proposed method in complex CCUS scenarios，and the proposed method provides a feasible optimization pathway and theoretical foundation for CCUS system planning.

As an essential link connecting resource potential and practical applications，the planning and design of microgrid，especially the rational configuration of the models and capacities of wind turbines，photovoltaic （PV） panels，and energy storage systems，is particularly crucial. To meet the load demand and reduce both investment costs and annual average comprehensive costs of microgrid，an economic capacity matching model considering the joint model selection of wind turbines，PV panels and energy storage equipment is proposed. Firstly，a microgrid system model is constructed，which includes wind turbines，PV panels，and energy storage. Secondly，a mixed integer linear programming model is designed with the objective function of minimal comprehensive costs of micro-grids is developed，which incorporates equipment selection constraints，capacity constraints，operation constraints，and power and energy balance constraints. Finally，the optimal equipment model combination and capacity configuration scheme are obtained using a commercial solver. The case study shows that compared with the benchmark schemes 2 and 3，the optimized scheme 1 reduces the investment cost by 21.01% and 17.25% respectively，and the comprehensive cost by 18.6% and 14.81% respectively，while meeting the same load demand. Therefore，the results prove that the proposed model can effectively accomplish the economic selection of equipment and capacity matching，reduce the investment cost and annual average comprehensive cost of microgrid，and provide the theoretical basis and technical support for the planning and design of microgrid.

With the increasing penetration of photovoltaic （PV） generation into power systems，the randomness and uncertainty of its output have raised higher requirements for the flexible peak regulation capability of grids. To offer more accurate predicted scenarios and facilitate flexibility oriented dispatch，an intelligent method integrating fuzzy clustering，similar day extraction，and probabilistic prediction was developed. Highly correlated meteorological variables including temperature，humidity，global horizontal irradiance，and tilted irradiance were first identified using the Pearson correlation coefficient. Fuzzy C-means （FCM） clustering was then applied to classify weather types. Feature weights were determined using the CRITIC method，and similar days within each weather category were extracted based on weighted Euclidean distance to construct a high quality training dataset. A quantile regression long short-term memory （QRLSTM） network was subsequently employed to perform short-term probabilistic forecasting of PV output. Simulation results demonstrated that the proposed approach achieved high prediction accuracy across various weather conditions，with confidence interval coverage rates exceeding 90% and significantly reduced confidence interval ranges compared to those of benchmark models. It was concluded that the proposed method effectively enhances the reliability and robustness of PV power prediction and provides high quality scenario support for uncertainty aware dispatch in multi-energy complementary systems.

The world is now in a critical period of energy structure transformation，oil and gas fields as large energy consumers are seen with accelerated green and low carbon transition. Electrochemical energy storage，as a vital technical category for steady applications of new energy such as wind and photovoltaic power in oil and gas fields，is considered increasingly important. This paper introduces the working principles and electrochemical characteristics and current research status of various electrochemical energy storage technologies （lithium iron phosphate，lithium titanate，flow batteries，lead-acid batteries，and supercapacitors）. According to their technical characteristics，their favorable scenarios，application scales and typical application cases have been sorted out，in terms of enhancing renewable energy consumption and optimizing traditional energy production and energy use. In view of the harsh environments of oil and gas scenarios featuring high risks，strong corrosion，and wide temperature ranges （-30~60℃），the challenges faced by the system and the problems that need to be solved urgently are analyzed in terms of the system safety，reliability，and environmental adaptability. This paper further elaborates the future development trend of each energy storage technology in oil and gas scenarios from the perspectives of new energy storage material systems，intelligent energy storage system management and equipment development. The findings of this research provide references for promoting the synergistic multi-energy development of wind and photovoltaic power and energy storage，forming a more efficient energy utilization system，and accelerating the green transformation of traditional energy.

In the context of the national strategy of "Dual Carbon"，CNPC innovatively proposes Green and Low-Carbon Action Plan 3.0 and establishes a three-step development strategy of "clean substitution，strategic replacement and green transformation". Supported by the high-quality integrated development of oil and gas and new energy，the strategy focuses on solving the dual challenges of energy industry development and carbon emission reduction and provides a practical path for the construction of a new energy system. As oil and gas and new energy belong to different energy fields，their integrated development is associated with numerous challenges，such as instability of efficient and low-carbon supply of oil and gas，insufficient support to replacement by new energy，and deficient depth of collaborative transformation of oil and gas and new energy. As an important hydrocarbon resource base in China，Xinjiang Oilfield play a key role in ensuring national energy security. It is imperative to leverage the inherent advantages of Xinjiang Oilfield and rely on three major paths，namely strengthening the green and low-carbon development of oil and gas，accelerating the development of new energy industry and enhancing the all-round security of oil and gas，and 12 measures，including energy conservation and efficiency improvement，clean substitution，regional energy supply，large-scale export，and basic research，to explore a green and low-carbon transformation path that is in line with the reality of Xinjiang Oilfield and has oilfield characteristics.

Given that the conventional five-arc trajectory design of the double-step horizontal wellbore may have no feasible solution in the case of limited horizontal section spacing，this study proposed a wellbore trajectory design method based on constrained optimization. By establishing a constrained optimization model to minimize the horizontal section length，an efficient solving algorithm was constructed，which combines the quasi-analytic solution and the bisection method. Given the failure problem that the singularity polynomial of the proposed quasi-analytic solution is always zero when the inclination and azimuth angles of the two horizontal sections are the same，a modified analytical calculation formula was proposed to deal with this theoretical defect of the traditional method. Compared with the traditional iterative method，the proposed method reduces the computational complexity to the order of solving quadratic equations via the characteristic polynomial dimension reduction strategy. Examples showed that this method can converge rapidly in cases of three-dimensional stepped wells，two-dimensional wells and simplified cases. By optimizing the adjustment of the horizontal section through the bisection method，the control of the minimum trajectory length under the constraint of wellbore curvature was achieved. This method can effectively deal with the trajectory design in cases of narrow spacing，like fault-separated reservoirs，and provide theoretical support for the development of drilling software. The research findings significantly improve the reliability and engineering applicability of the trajectory design for stepped horizontal wells.

The investment estimation of a systematic drilling engineering project is an important step for oilfield enterprises to strengthen investment control and enhance operation management. The quality of investment estimation does not only decide the feasibility and profitability of the development plan，but also has an important instruction influence on the implementation and operation performance of the approved engineering plan. This paper proposed a method for extracting engineering parameters of drilling investment estimation based on the natural language processing algorithm and the Monte Carlo simulation investment prediction model. These two techniques were introduced into the petroleum engineering estimation，and it was demonstrated via modelling and case studies that all selected control factors were significant and thus effective. Based on the above，the investment estimation was carried out. Natural language processing algorithms were required for parameter extraction and processing，with an accuracy of over 90%. Meanwhile，the Monte Carlo simulation investment prediction model was used for calculation to ensure that the error between the extreme investment and the existing economic evaluation results was less than 5%. This developed method has been successfully applied to 29 production capacity building projects in 2024，identifying and warning 8 projects with excessive investment. It improves the accuracy and efficiency of engineering parameter extraction，enhances the percent of pass for the internal rate of return of petroleum drilling engineering investment estimation，and is of great help in improving the digitalization level of the petroleum engineering estimation.

The downhole monitoring system，integrated into the conventional electric control downhole flow control valve for intelligent wells in China，cannot monitor the two key parameters，namely the flow rate and water cut. Moreover，once the driving mechanism fails，the transmission screw automatically locks the sliding sleeve at the current position，making it impossible to close or fully open the sliding sleeve in a timely manner and resulting in the inability to regulate the production of the target layer or branch. In this research，a unique sliding sleeve mechanical structure with an integrated downhole parameter measurement system was designed using the selected sensors of pressure ，temperature and water-cut，flow meter，and downhole sliding sleeve displacement sensor，to solve the incapabilities of existing electrical-control downhole flow control valves in China to monitor fluid flow and water cut. A unique mechanical transmission system was designed using the scalable coupling to serve as the driving mechanism for the concentric sliding sleeve. The designed sliding sleeve integrates a force-open force-close mechanical structure，which can be moved to the fully open or fully closed position by the sliding sleeve switch tool. This eliminates the shortcomings of the mechanical structure of conventional electric control downhole flow control valves in China and provides key support for the development of the intelligent well technology in China.

In cable logging operations，accurately regulating the cable tension is crucial to ensure the safe arrival of the logging instruments at the wellbore bottom and accurate data acquisition. In order to precisely predict the change of cable tension during well logging，a well logging cable tension prediction system based on the hybrid model was designed，which combines the physical model with in-depth understanding of the mechanical nature of the logging process and the data-driven model SC-PBiGRU with advantages in data processing and analysis. The system was validated using a large number of well logging data. The system can keep the maximum error of the prediction results within 5% and deliver stable prediction accuracy under complex geological conditions and equipment status. It is a powerful tool to provide technical support for tension regulation in cable logging operations.

The emergence of large language models（LLM） with characteristics of general artificial intelligence has ushered in a milestone technological revolution across industries，offering new opportunities for the intelligent transformation of petroleum engineering. This paper explores the application prospect，challenges，and development recommendations for LLM，represented by DeepSeek，in petroleum engineering. First，the fundamental concepts and technical features of LLM are introduced. Subsequently，potential application scenarios in petroleum engineering are examined，including user interaction and Q&A systems，data governance and information integration，data analysis and decision support，information parsing and intelligent assistance，and environmental monitoring and safety management. Concurrently，limitations and challenges in applying LLM to petroleum engineering are identified，such as insufficient knowledge updating capabilities，difficulties in comprehending domain-specific expertise，limited innovation in scientific research，and high training costs. Finally，recommendations and future directions for leveraging LLM in petroleum engineering are proposed，including developing specialized LLMs tailored for petroleum engineering，constructing petroleum-domain databases and information extraction frameworks，integrating internet-enabled search and real-time updating functionalities，and advancing image processing and video generation technologies. This study systematically outlines an implementation framework for LLM in petroleum engineering，providing theoretical guidance and practical references for the industry’s intelligent evolution.

Accurately identifying the damage failure modes and causes of PDC cutters and PDC drill bits is a key step in the drilling tool selection and the drill bit iterative optimization. To improve the accuracy and objectivity of drill bit damage identification，failure analysis was conducted on hundreds of PDC bits tripped out of wells，and the main damage failure modes and causes of PDC cutters (including various shaped cutters) were summarized，leading to a dataset containing over ten thousand images of PDC cutter damage morphologies. Then，based on the convolutional neural network-based YOLOv7 image recognition algorithm，an intelligent recognition model for PDC cutter damage failure was established. This model can effectively infer damage types from PDC cutter images and automatically annotate the images with corresponding damage failure modes. The model was evaluated using multiple performance metrics，showing an identification accuracy of over 80%. Furthermore，this model was combined with the PDC drill bit design theory and damage failure mechanisms to develop a new intelligent recognition method for PDC drill bit damage failure，using statistical methods like causal inference. This method can automatically evaluate the damage failure modes of PDC cutters in different regions of the bit crown using only photos of bits tripped out of wells and determine the primary cause of PDC drill bit failure. The research findings provide references for intelligent drill bit damage identification and innovation in intelligent drilling technology.

Stuck pipe incidents significantly disrupt drilling operations and cause major economic losses. Traditional physics-based models for stuck pipe prediction and analysis are subjective with large errors，while intelligent models suffer from high false alarm rates and low interpretability. To address these issues，an unsupervised stuck pipe risk evaluation method based on fuzzy mathematics was proposed. This approach involves：1） establishing a tubular mechanics model to quantify wellbore friction characteristics；2） constructing a deep autoencoder to detect abnormal parameters through reconstruction error analysis；and 3） developing a dual-factor membership function for a comprehensive fuzzy evaluation of friction coefficient trends and reconstruction errors. This method avoids the dependence of the conventional supervised learning on labeled data，integrates the interpretability of mechanistic models with the generalization ability of data-driven models，and creates a physics-constrained intelligent risk assessment framework. Tests using real drilling data show that this model effectively identifies early signs of stuck pipe. It improves warning accuracy by 7.1%，compared to the single-parameter methods，reduces false alarms，and delivers a 30-minute-earlier alert. The proposed method provides a promising new technique for predicting downhole complex issues and possesses significant application potential.

In drilling engineering，stuck pipe，as one of the common downhole complex issues，seriously affects drilling efficiency. Stuck pipe monitoring is crucial for ensuring the safety and efficiency of drilling operations. With the rapid development of artificial intelligence technology in recent years，new approaches have emerged for stuck pipe monitoring. However，the existing research on intelligent stuck pipe monitoring mainly focuses on the optimization and application of single unsupervised or supervised algorithm，leaving a gap of systematic comparative studies on these two types of algorithms with respect to stuck pipe monitoring. This study selects multi-dimensional drilling parameters such as bit position，hook height，and torque of ratary table as the study targets，according to distance correlation coefficients，constructs a comparative evaluation system involving classic unsupervised algorithms （AE，K-means，DBSCAN） and supervised algorithms （SVM，RF，LSTM），and analyzes the performance of these algorithms in estimating stuck pipe trends. The results show that compared with supervised algorithm，unsupervised algorithm delivers a increase of 12.5% in monitoring average accuracy and reductions of 37.1% and 27.6% in average false and missed alarm rates respectively. Unsupervised algorithm demonstrates greater advantages in cases of small sample sizes and absence of mechanistic constraints. The findings of this research provide references for model selection and optimization in intelligent stuck pipe monitoring for drilling engineering and promote the practical application of unsupervised algorithm in stuck pipe risk monitoring.

es and advantages/disadvantages of different models in terms of early warning capabilities. It is found that in scenarios where the demand for characteristic parameters is low and the data sources are stable，machine learning algorithm models exhibit superior accuracy and timeliness in the early warning of drilling complex accidents. However，when faced with challenges such as high computational complexity，poor data quality，and unstable data sources，especially in predicting lost circulation during drilling and early-warning complex well kick accidents，the models suffer from high rates of false alarms and frequent missed alarms，and few field application cases are reported. To promote the field application of drilling complex accident early warning techniques and drilling digitalization，it is necessary to strengthen research on data quality improvement and algorithm optimization. Despite the numerous challenges，big data and artificial intelligence still open up broad prospects for early warning technologies.

Bimetallic composite piping technology is an important method to solve the internal corrosion of pipelines of the gathering and transportation system of oil and gas fields. The forming，welding and testing are the prerequisites for safe pipeline operations. To ensure the safe production of oil and gas fields，the progress of the forming，welding and non-destructive testing （NDT） technologies of bimetallic mechanical composite piping was reviewed. Two commonly used mechanical molding methods and their characteristics were clarified，the process methods for improving the quality of welded joints were analyzed，and the NDT technologies for different pipeline defects were summarized. The results show that in terms of pipe forming，explosive forming and hydraulic forming are commonly used in China for composite piping，but they still have limitations in manufacturing large-diameter pipes and special-shaped pipe fittings；in terms of welding，the quality of welded joints can be improved by optimizing the welding process，and the laser cladding technology of pipe ends has become a future research direction；in terms of the NDT，traditional testing methods are gradually developing towards intelligent and integrated modern technologies，delivering a wider coverage and higher defect detection rates. In addition，if the pipe end measurements at key steps of the full life cycle of mechanical composite piping are recorded，accurate traceability can be achieved once quality problems occur. It is concluded that improving the quality control of mechanical composite piping technology during the forming and welding processes and the accuracy of the NDT technologies is of great significance for their applications in oil and gas field gathering and transportation.

In order to solve the problem of severe blockage caused by the gradual precipitation，aggregation and settlement of asphaltenes with the decreasing temperature during the artificial lifting process in Tahe Oilfield，a high-efficiency asphalt dispersant was developed and evaluated via the steel wire mesh dissolution method. Through the characterization analysis of the wellbore sediments by three-component solvent fractionation，elemental composition determination and scanning electron microscopy （SEM），asphaltenes were determined to be the main component of Tahe wellbore sediments. According to the principle of similar mutual solubility ，a dispersant LYH-1 （aromatic solvent LY + 1.0% n-pentanol + 1.0% nonylphenol + 0.2% petroleum sulfonate） that could efficiently dissolve asphaltenes was developed. The asphaltene sediments were soaked in the asphalt dispersant LYH-1 in a water bath at 50°C for 4 h，and the solubility of 1 g of asphaltene sediments in 5 g of asphalt dispersant LYH-1 was as high as 97%，and the sediments did not aggregate after long-term standing，suggesting excellent stability and expanded applicability. The investigation of the working mechanism of the high-efficiency asphalt dispersant LYH-1 demonstrates that the dispersant forms a stable system with asphaltene sediments，mainly through hydrogen bonding and π-π interaction，which reduces the particle sizes of asphaltene aggregates to allow them to be stably suspended in solutions，and hinders the further flocculation and deposition of asphaltenes. The results show that LYH-1，as a novel high-performance asphalt dispersant，can effectively prevent the blockage of oil wells and surface pipelines while reducing production costs，so as to achieve the goal of production growth and improve the development efficiency of heavy oil reservoirs.

In a certain area of Karamay Oilfield，numerous production wells suffer from rapid water cut rise and high water cut after fracturing treatments. To solve this problem，the proppant grafted with the hydrophobic association relative permeability regulator，RPM-SiO₂，was developed by grafting the hydrophobic association relative permeability regulator onto the quartz sand surface，with the help of silane coupling agents KH570. The grafting of relative permeability regulators onto the proppant surface was confirmed successful by infrared spectroscopy and electron scanning microscopy （SEM）. Under the reservoir conditions of the study area of Karamay Oilfield，the differences of conventional performance （wettability，density，acid solubility and compressive strength），fracture conductivity，and water control ability between RPM-SiO₂ and blank quartz sand proppants were investigated. The results show that the comprehensive performances of RPM-SiO₂ and quartz sands are basically consistent，both meeting the requirements of the industrial standard. The resultant oil phase fracture conductivities are consistent，but the water phase fracture conductivity of RPM-SiO₂ is 25% lower than that of quartz sands. Compared with quartz sands，RPM-SiO₂ presents a decrease of 83.41% in the water phase permeability，17.49% in the oil phse permeability，and 18.65% in the water cut of produced liquid. RPM-SiO₂ has high water control capability and long-term effectiveness.

Significant casing deformation （CD） occurs during multi-stage fracturing of shale gas horizontal wells，which reduces the ratio of recovered reservoirs and increases operation costs. Based on a comprehensive review of global research on this issue，a comparative analysis of the current status of casing deformation in shale gas horizontal wells was conducted. With the casing deformation data from Changning-Weiyuan，Luzhou，and Weirong blocks，the distribution patterns of casing deformation in terms of time，space，and morphology were summarized. The influences of engineering factors such as casing and cement sheath types，cementing quality，fracturing and perforation parameters，and thermal stresses，as well as geological factors such as reservoir heterogeneity and reservoir slip，on casing deformation，were analyzed. The analysis results indicate that while engineering factors can increase casing stresses，they are unlikely to cause casing deformation. Among geological factors，reservoir slip induced by natural fractures and faults activated during multi-stage fracturing is the main controlling factor leading to significant casing deformation. To address this issue，various control methods were summarized，including optimizing casing and cement sheath parameters，improving cementing quality，selecting appropriate fracturing and perforation parameters，optimizing wellbore trajectory，and controlling reservoir slip. Additionally，it was proposed to enhance the understanding of formations and improve prediction accuracy of reservoir slip. The research findings provide references for casing integrity design and control during the fracturing process.

Shale reservoirs are characterized by low porosity，low permeability，and difficulty in exploitation，typically requiring the development approach combining long horizontal wells with large-scale volume fracturing techniques. After the fracturing fluid enters the formation，it undergoes a series of physical and chemical reactions with the reservoir，where salt ion diffusion plays a significant role. However，the existing research on the mechanism of ion diffusion and its application to diagnosing hydraulic fracture network is still imperfect. Therefore，this paper combines theoretical analysis with field cases to summarize the sources of salt ions in shale reservoirs，and the characteristics，mechanisms and influencing factors of ion diffusion，and presents an example of diagnosing hydraulic fracture network based on salt ion diffusion. The sources of salt ions in shale reservoirs include dissolved salts in the water film on the pore walls，crystallized salts from hydrocarbon generation and water expulsion，and salts produced by water-rock interactions. The characteristics of ion diffusion are similar to the imbibition process，which is divided into three stages：initial，transitional，and late diffusion. The initial ion diffusion rate is relatively high，exhibits a linear relationship on a logarithmic time scale，and follows Fick's law and the Einstein-Smoluchowski equation. The factors affecting salt ion diffusion include reservoir properties，solution properties，and other factors such as temperature and viscosity. Saltion diffusion can be used for the diagnosis of the development degree of volume fracturing fracture network. The method of diagnosing hydraulic fracture network through salt ion diffusion can provide scientific guidance for shale reservoir fracturing design and fracture network evaluation，help to deliver more accurate and effective reservoir stimulation and promote the efficient development and utilization of shale oil and gas resources.

The horizontal well of Jimsar shale oil with a long openhole wellbore adopts the two-casing-section structure，and the openhole wellbore of the second casing section is 4 000 m long，with a horizontal wellbore over 2 000 m. The used drilling fluids are oil-based，and wellbore collapse tends to occur when drilling the Badaowan and Jiucaiyuanzi Formations and leads to movement resistance，sticking of tools，lost circulation，etc. To overcome the wellbore collapse in complex formations，in accordance with the lithological characteristics of formations，the main factors affecting wellbore stability such as clay mineral composition and micro-fracture development were analyzed，the mechanisms of wellbore instability of such collapse-prone formations were clarified，and the anti-collapse theory of oil-based drilling fluids was developed，which features "multi-element cooperation and broad-spectrum plugging". Based on the proposed theory，the anti-collapse formulation of oil-based drilling fluids was improved by optimizing the materials such as asphalt products，ultra-fine calcium carbonates and nano-plugging agents. The laboratory tests show that the performance parameters of the drilling fluids meet the operation requirements and the plugging performance is excellent. Specifically，the drilling fluid density is 1.52-1.62 g/cm³；funnel viscosity，80-100 s；yield point，8-13 Pa；emulsion-breaking voltage，above 500 V；oil-water ratio，（80：20） to （85：15）；API fluid loss，≤ 1.5 mL；HTHP fluid loss at 120°C，≤ 2 mL. The presented anti-collapse system of oil-based drilling fluids has been successfully applied to Jimsar shale oil horizontal wells with a long openhole wellbore. The average borehole enlargement rate of the openhole wellbore and the rate of downhole complex issues were 3.03% and 0.55% respectively. The anti-collapse system effectively ensured the drilling safety of the build-up and horizontal wellbores.

Longdong Oil Block requires the full implementation of drilling fluid non-landing technology to promote the recycling of waste drilling fluid. In order to solve the problem that the performance of water-based drilling fluids prepared using on-site hydraulic filtrate waste cannot meet the standards and the influencing factors are not clear，the ethylene diamine tetraacetic acid（EDTA） titration，bacterial plate counting method and atomic absorption spectrometry （AAS） were used to investigate the key techniques to improve the reuse rate of hydraulic filtrate waste. The experiments show that the high content of calcium and magnesium ions，bacteria，and heavy metals are the main reasons for the poor performance of water-based drilling fluids prepared using hydraulic filtrate waste. Correspondingly，the modified coagulation and precipitation complexing agent II，polyether demulsifier JX，and flocculants ZY-I，ZY-II have been developed to perform the flocculation-precipitation-sterilization treatment together with the sterilizing agent. The resultant average removal rate of calcium and magnesium ions is 95.5%，the sterilization rates of saprophytic bacteria （TGB） and sulfate-reducing bacteria （SRB） are 96.54% and 100% respectively，and the heavy metal content is less than 2.31 μg/L. The laboratory tests of recycling of hydraulic filtrate waste and water-based drilling fluid preparation have been completed for 6 wells in Longdong Oil Block. Longdong Oil Block waste drilling fluid hydraulic filtrate recycling technology has been formed and applied in 5 wells of this block. The water-based drilling fluids prepared using the recycled hydraulic filtrate waste presents a performance in line with the drilling engineering design requirements，facilitating the smooth drilling process，effectively protecting the environment and saved water resources，demonstrating good prospects for application promotion.

Lost circulation is a common and challenging downhole complex issue in current drilling operations. It has become one of the major factors affecting drilling speed and may lead to safety incidents of different levels. By comprehensively analyzing the types and mechanisms of lost circulation，the performances of global novel plugging materials under different operating conditions，and their interactions with factors such as the wellbore and formations，this study elucidates the characteristics and mechanisms of cement，cross-linking system and metallic plugging materials，granular and fiber lost circulation materials （LCMs），and the combination of curable materials and LCMs. The application performances and pros and cons of different types of LCMs for lost circulation in various formations are summarized. The results indicate that given both the treatment success rate and cost-effectiveness，cement plugging materials are preferred for handling fluid loss caused by the highly permeable rock matrix，with a treatment success rate of 91%. To address the karst-cavern thief zone，curable materials with LCMs are relatively favored，delivering a treatment success rate of 89%. Fiber LCMs are preferred for treating natural fracture-type lost circulation，with a treatment success rate of 75%. When dealing with the induced fracture-type lost circulation，granular LCMs are favorable，with a treatment success rate of 92%. The findings of this research are of important theoretical and technical guiding significance for enhancing the plugging performance of drilling fluids and promoting the development of lost circulation plugging technology.