Mud logging technology has the four advantages of "more,faster,better,cheaper",but the development of this industry is still facing the four challenges of "weak basic theory,insufficient advanced technology,shortcomings in technical services,and poor development ecology". It is urgent to grasp the source of "thinking mode" to drive the benign development of mud logging technology innovation. Therefore,this paper puts forward three basic thinking modes of theoretical thinking,system thinking and in-situ thinking that should be followed in the innovation of mud logging technology. Theoretical thinking includes three levels：application of theory,extension of theory and innovation of theory. System thinking includes three levels：technology chain thinking,technology series thinking and technology system thinking. In-situ thinking includes two levels：in-situ thinking of hydrocarbon reservoirs and in-situ thinking of geology-engineering integration. These three thinking modes complement each other and constitute the cornerstone of innovative thinking in mud logging technology. These basic thinking modes have a certain guiding and promoting role in enriching the mud logging theory system,deepening the mud logging technology system,improving the mud logging services system,and perfecting the mud logging ecosystem.

Western oilfields such as Xinjiang Oilfield and Tarim Oilfield cover vast territories. Due to communication signal coverage limitations in traditional transmission networks, data collected at some well sites cannot be transmitted back in a timely manner. This has certain impacts on optimizing drilling operations at the frontier well sites, real-time monitoring of drilling operations at the rear base, and geological interpretation research. To address the challenge of real-time mud logging data transmission caused by insufficient network coverage, this paper proposes a real-time mud logging data transmission system based on Beidou short messages. By analyzing the Beidou 3 satellite navigation system transmission protocol, constructing a Beidou mud logging data transmission test environment, and developing Beidou mud logging data real-time transmission system, an integrated closed-loop transmission system for mud logging data "acquisition-encoding-transmission" has been achieved. This research not only resolves traditional network dependency issues but also reduces energy data security risks through the autonomous controllability of the Beidou protocol. It provides highly reliable, low-cost communication technology support for oilfield digital transformation and offers a practical example for the large-scale application of the Beidou system in the energy sector.

The development of drilling technology has greatly improved drilling efficiency,but it has made it difficult for traditional naked eye debris identification methods to meet efficient logging. In addition,the differences in the technical level of field personnel have seriously restricted the improvement of debris logging quality. Therefore,a digital intelligent identification system for debris that integrates artificial intelligence,image analysis and Internet of things technology has realized automated collection,real-time processing and intelligent interpretation of debris data. This technology integrates high-resolution image acquisition,digital image feature extraction,and an AI lithology classification model based on deep learning. Practical application in Changqing Oilfield shows that the lithology identification accuracy of the debris digital intelligent identification system has been increased to more than 90%,effectively solving the problem of difficulty in naming micro rocks in traditional manual identification. The system not only significantly improves the accuracy and efficiency of cuttings logging,but also provides key technical support for the transformation of logging operations from empirical to intelligent,which has important practical significance and broad application prospects for improving the overall logging quality.

Rock hardness and plasticity coefficient are important indicators for oil drilling, and the method of obtaining these indicators by core experiments is limited due to the difficulty and high cost of full scale core coring. Based on this background, the cores of Qingshankou Formation in an oilfield are selected to construct data sets of hardness, plasticity coefficient and element characteristics through conducting static load indentation experiments and XRF element experiments. The Pearson correlation analysis and the algorithm of particle swarm optimization BP neural network （PSO-BP） were used to reveal the main controlling elements of rock hardness and plasticity coefficient, and a method of shale hardness and plasticity coefficient evaluation while drilling based on XRF element logging was established. The predictive results show the major elements for main controlling shale hardness are Fe, Al, K and Ca, and the trace elements are Cr and Rb, shale hardness is positively correlated with Ca element and negatively correlated with other main controlling elements. The major elements for main controlling plasticity coefficient is Ti, and the trace elements are Cd, Nb, Ni and V, plasticity coefficient is negatively correlated with Ti and positively correlated with other main controlling elements. The network error of the shale hardness prediction model is 8.06×10^-8, and the network error of the plasticity prediction model is 3.02×10^-11, both of which are below the preset thresholds. From the application of this method in tracking while drilling shale oil, it can be known that the shale host in the work area belongs to the low-plasticity rock of medium-soft grade 3, so the suitable PDC drill bit is recommended, and a high penetration rate is obtained. The method provides technical support for drilling dynamic optimization.

With the deepening of exploration and development of oil and gas resources, it is more important to accurately monitor the three pressures of formation （pore pressure, collapse pressure and fracture pressure）. However, although the traditional formation three-pressure monitoring method has been widely used, it has the limitation of relying on human experience and parameter setting. In order to realize the real-time and accurate monitoring of formation three pressures, this paper takes four wells to be monitored in Beidagang buried hill structural belt of Huanghua Depression as an example. Based on the drilling, recording and logging data of completed wells around the wells to be monitored, combined with advanced machine learning algorithms such as Extreme Gradient Boosting （XGBoost）, light Gradient Boosting Machine （LightGBM） and Random Forest （RF）, the drilling and logging data are coupled with the logging calculation pressure based on poroelastic mechanics theory. The results show that the pore pressure prediction average relative error of all measured pressure points in the study area is 6.32%, and the overall monitoring accuracy is over 93%. The multi-parameter coupled formation three-pressure monitoring technology has high prediction accuracy, good generalization performance and feasibility. In view of the fact that this method can achieve accurate monitoring of three pressures while drilling in multi-lithologies, multi-types of reservoirs, and multi-pressure genesis formations, it can be popularized and applied to three pressures while drilling monitoring in other complex oil and gas reservoirs, providing technical support for integrated risk prediction and safe and efficient drilling construction of geological engineering.

During the monitoring of the outlet drilling fluid parameters at the drilling site,due to the fast flow velocity and strong impact force of the drilling fluid returning from the well bore,along with the deposition of cuttings,it often leads to the sensor not being installed vertically and the probe being buried,resulting in large measurement parameter errors,which affect the discovery and evaluation of the show of gas and oil and wellbore safety. Therefore,based on the principles of automation control and quantitative acquisition technology of drilling fluid,a quantitative monitoring system for outlet drilling fluid parameters has been researched and developed. By optimizing the working environment and monitoring methods of the sensors,this system can ensure that the outlet temperature,density and conductivity sensors achieve quantitative monitoring under the optimum working conditions,effectively solving problems such as substandard working conditions at the well site. It has been applied to 32 wells in Tuha,Xinjiang,Sulige and other oil and gas fields,which has significantly improved the accuracy of monitoring outlet drilling fluid parameters and has provided reliable technical support for wellbore safety control in the process of oil and gas field drilling and subsequent hydrocarbon resources development and evaluation.

To meet the strict requirements for pressure measurement accuracy in the petroleum industry production field and address the limitations of traditional pressure gauge calibration methods,high-precision pressure sensors,automation control technology,machine vision and image processing technology are applied to develop and design the intelligent calibration device from both hardware and software aspects. The hardware focuses on the key lectotype and architecture construction of modules such as pressure sources and sensors. The software implements functions such as data acquisition,processing,storage,and automatic calibration process. Field tests and applications show that the device features high calibration accuracy,good stability and convenient operation. It can significantly improve the efficiency of pressure gauge calibration,ensure the quality of pressure gauge,and provide strong technical support for petroleum measurement work.

To tackle the limitations of ultrasonic wave liquid level sensors in drilling fluid outlet buffer tank level monitoring at oilfield drilling sites, which particularly include susceptibility to environmental interference and insufficient measurement accuracy. The improvement plan for 78 GHz Frequency-Modulated Continuous Wave （FMCW） radar liquid level sensor is proposed in this study, which achieves millimeter-level precision （error of ±3.2 mm） with narrow （≤6°） by optimizing beam angle and anti-jamming algorithms. Application to well W 204HX-X in Southwest Oil & Gas Field demonstrated that superior performance: compared to ultrasonic wave sensors, the radar sensor improved measurement accuracy by 79.6% and data stability by 16.2% under severe liquid surface fluctuation conditions. The technology effectively overcomes measurement deviations caused by high-temperature smoke and water mist interference while enhancing monitoring stability.This research reveals and expands the applicability boundaries of high-frequency radar technology in complex industrial environments. Both cost-benefit analysis and functional evaluations confirm its viability as a replacement for traditional ultrasonic wave level sensors. The findings provide a novel technical pathway for intelligent drilling fluid level monitoring equipment development in oil and gas drilling operations.

In view of the shortcomings of traditional formation pore pressure monitoring methods in the strata with strong hydrocarbon generation pressurization effects, a new method for discriminating formation pressure trend based on synergistic coupling of formation pore pressure monitoring technology and diffuse reflectance infrared Fourier transform spectroscopy（DRIFTS） technique is proposed. During the process of formation pressure monitoring while drilling, the characteristics of logging parameters （such as dc index, interval transit time, resistivity, etc.） deviating from the normal trend line are used to identify abnormal pressure formations. At the same time, DRIFTS technique is introduced to rapidly analyze the mineral composition, total organic carbon content （TOC） and vitrinite reflectance （R_o） of cuttings samples, revealing the hydrocarbon generation pressurization effects of organic matter. Taking well B in Wenchang A Sag of Pearl River Mouth Basin as an example, a chart was constructed through the synergistic coupling of formation pressure and DRIFTS techniques, and then 4 350 m was identified as the inflection point of hydrocarbon generation pressurization, and it was found that the rising trend of formation pore pressure was highly consistent with the increasing trend of TOC and R_o, which verified the effectiveness of the synergistic discrimination method. Compared with the traditional models, this method can simultaneously quantify the overpressure contributions of undercompaction and hydrocarbon generation, significantly improving the pressure discrimination accuracy of complex overpressure mechanism formations. The high-resolution analysis ability of DRIFTS technique for minerals and organic matter, dynamically combined with the data of pressure monitoring while drilling, provides more reliable formation pressure prediction and safety guidance for drilling engineering, and has important field application value.

The shale oil layers of the third member of Shahejie Formation in Qikou Sag has higher clay mineral content, stronger water sensitivity than that of Ek₂ of Cangdong Sag, developed fracture system, and extremely complicated engineering in the drilling process. Since the use of white oil-based drilling fluid in horizontal wells in the third member of Qikou Shahejie Formation in 2023, drilling and development efficiency has been significantly improved, but it has a great impact on gas logging. By comparing and analyzing the response characteristics of gas logging under water-based and oil-based drilling fluids, this paper summarizes the adsorption characteristics of oil-based drilling fluids to total hydrocarbons and hydrocarbon components under different gas kick degrees, and based on the data, the measured relative percentage change rate of each component, the gas logging correction method is studied, and the gas logging interpretation chart and evaluation standard are established, which provide the basis for the evaluation of shale oil sweet spots under oil-based drilling fluid,and have certain guiding significance through the verification of production effect.

During drilling operations, the penetration of the drill bit into the target formation and the occurrence of formation penetration can be determined by monitoring changes in the ion concentration of the drilling fluid. However, conventional manual chemical titration measurements suffer from lengthy operation cycles, significant errors, and substantial influence from human factors. The ion selective electrodes （ISE） method employed by some laboratories suffers from significant measurement inaccuracies influenced by pH and temperature, rendering it unsuitable for field applications. This paper therefore proposes an error compensation method for ISE measurements affected by drilling fluid pH and temperature interference. Building upon an overview of ISE measurement principles, the paper analyzes the influence characteristics of pH and temperature parameters on ISE and establishes an experimental scheme for chloride ion concentration measurement. Subsequently, based on experimental data and model analysis of pH and temperature, linear compensation terms for pH and temperature are introduced into the Nernst equation to eliminate interference from pH and temperature variations in the solution to be measured. This establishes pH and temperature compensation models for ion selective electrodes. Finally, the models are validated using ion concentration parameters are actually collected at different temperatures and pH values. After compensation, the measurement errors for chloride ion concentration are consistently within 10%, meeting field requirements.

Baoding Sag is currently a key play for exploration and development. Due to the reservoirs with shallow burial depth of oil reservoirs in the region,there are not only characteristics of low-mature oil reservoirs such as high methane content and high oil density,but also widespread phenomena of biodegradation and water washing damage,making the gas composition characteristics no longer sensitive to evaluation,and the level of real object show is relatively high. In mud logging evaluation and analysis,parameters such as P_g are all affected to a certain extent. The existing mud logging interpretation and evaluation techniques show certain limitations,resulting in decreased applicability. To effectively solve the problems of the complex mud logging response characteristics of the reservoirs and difficult identification of reservoir fluid properties,the sensitive parameters were extracted by integrating relevant influencing factors through oil testing and productivity determination data as well as various analysis and testing data. Statistical analysis software was used to classify and discriminate,and a linear regression model was constructed. It has made the coincidence rate of mud logging interpretation while drilling reach 73.33%,meeting the need for rapid reservoir fluid property evaluation while drilling and meeting the conditions for on-site promotion and application,simultaneously providing support for the digital and intelligent transformation of mud logging industry.

The shale gas resource potential of Wujiaping Formation in Hongxing area,the eastern margin of Sichuan Basin is large,but the production capacity of each well varies significantly,and the influencing factors have not been systematically quantified. For the Analytic Hierarchy Process （AHP） can effectively realize the quantitative evaluation of multi-factors, the first-level index layer of geology and engineering factors is established, covering 5 second-level index layers of trajectory factor,physical property factor,gas storage factor,fracturing factor,gas test factor,and 21 third-level indexes such as the horizontal section length, the total gas content,the fracture pressure,and backflow volume,etc.The judgment matrix is constructed and the indicator weight for each layer is calculated. Typical single wells in Hongxing area are selected,and the standardized values of each indicator are multiplied with the weights calculated by AHP to get the comprehensive evaluation value of each well,and fitted with the open flow potential and recoverable reserves to verify the reliability of the model. The results show that the weights of methane content,open pressure and organic carbon content are 0.121 8、0.111 1 and 0.088 9 respectively,which are the main control factors of gas-well deliverability. The comprehensive evaluation value of each well fits well with the open flow potential and recoverable reserves,and the fitting degree is higher than 85%. Through this study,the key control parameters of shale gas wells are clarified in Wujiaping Formation in Hongxing area,which can provide theoretical basis for the efficient development of this area.

As a new type of unconventional energy, coal-rock gas has attracted much attention in its exploration and development. However,the chemical composition of coal-rock gas reservoirs is complex,which affects gas content,adsorption capacity,and development effects. Traditional laboratory analysis and logging methods are high cost, long cycle length,and difficult to adapt complex well conditions. It is difficult to meet the needs for efficient development of deep coal-rock gas,which further highlighting the urgent need for efficient and accurate dynamic evaluation methods. This research takes coal rocks from the Carboniferous Benxi Formation and Permian Shanxi Formation in the central-eastern part of the Ordos Basin as the object,and proposes a method for comprehensively evaluating the industrial components of coal rocks based on X-ray element logging technology and gas logging total hydrocarbon data. By analyzing 36 coal-rock samples,a linear positive correlation model between major element content and ash content, as well as a linear negative correlation model with fixed carbon are constructed. Considering that volatile component and moisture are controlled by the pyrolysis of organic matter,the dynamic inversion of volatile component and moisture is realized by introducing gas logging total hydrocarbon data. The model was applied to Wells M 172 and WT 1,providing guiding data for reservoir reconstruction,with gas test yields reaching 13.6×10⁴ m³/d and 10.4×10⁴ m³/d respectively. This method breaks through the limitations of traditional laboratory analysis and logging methods,which can analyze and evaluate the industrial components of coal rocks in complex well types （horizontal wells,highly-deviated wells） in real time,and provides low-cost and high-efficiency technical support for deep coal-rock gas exploration.

Aiming at the problems of complex geological conditions of deep coal rock, easy collapse of target coal rock, difficult logging operation, limited log information, and immature comprehensive evaluation of mud logging reservoir quality, and relying on the key mud logging parameters of more than two new wells in Changqing Oilfield in recent two years, this paper establishes a set of deep coal-rock gas reservoir quality evaluation technology based on mud logging technology from four aspects： rock quality, source rock quality, gas quality and engineering quality. This evaluation technology has been successfully applied to the fracturing layer selection scheme design of 15 deep coal-rock gas wells in Changqing Oilfield, highlighting the technical advantages in comprehensive evaluation of mud logging and achieving deep fusion of geology-engineering integration. This technology effectively meets the exploration and development needs of deep coal-rock gas reservoirs, provides reliable technical support for horizontal well trajectory optimization and fracturing layer optimum selection, and verifies its strong advantages in deep coal-rock gas evaluation.

The "dual carbon" strategy has accelerated the energy transition and the development of new energy in the petroleum industry. Currently,a certain number of long-closed oil and gas wells remain in major oilfields. Repurposing these wells into geothermal wells can revitalize assets,reduce production costs,and serve as a critical measure for clean energy substitution. Taking Shenjiapu Oilfield in Cangdong Sag, Dagang Oilfield as an example,the distribution characteristics of the Guantao Formation thermal reservoir are systematically analyzed by collecting and organizing drilling and geological data. The geothermal resource quantity is evaluated by using the thermal reservoir volumetric method and 3D geological modeling,and a quantitative evaluation method for the potential of converting long-closed oil and gas wells into geothermal wells is established. The research results indicate：The Guantao Formation thermal reservoir in the study area features significant stratum thickness,moderate depth,stable distribution,and high potential,primarily hosting medium-to-low temperature hydrothermal resources. The thermal reservoir temperature ranges from 49.6 to 64.3 °C,with a total geothermal resource of 0.13×10¹⁸ J,geothermal water resources of 2.9×10⁸ m³,geothermal water heat of 0.05×10¹⁸ J,and a geothermal resource abundance of 15×10¹⁵ J/km²,indicating rich thermal reservoir resources. Ten evaluation factors,including structural feature, thermal reservoir buried depth, thermal reservoir thickness and thermal reservoir temperature,were selected to establish a quantitative index （Z_i）for evaluating the potential of converting long-closed wells into geothermal wells. The wells were classified,and six Type Ⅰ wells with Z_i more than 80,representing superior geothermal resource conditions,were prioritized for implementation. The pilot test on Well J-9 demonstrated a maximum allowable geothermal water exploitation of 55.46 m³/h from the Guantao Formation,indicating medium production capacity. These findings provide critical support for deepening the understanding of the Guantao Formation thermal reservoir in Shenjiapu Oilfield and Dagang Oilfield as a whole,as well as for promoting the large-scale development and utilization of geothermal resources in oilfields. This study offers valuable insights for sustainable oilfield utilization and the advancement of clean energy.

Point dam sand bodies, as the core reservoir space in the sedimentary system of X block meandering rivers, have complex and variable internal architectures and spatial distribution characteristics, the sheet-like thick sand members formed by external genetic control are difficult to divide. Therefore, the analytic hierarchy process for reservoir architecture was adopted. Based on the spatial combination characteristics of sand bodies and their cause classification, the distribution range of effective reservoir composite meander belts in meandering rivers was determined with sand-mudstone as the boundary. From the composite meander belts, single channel sand bodies were identified. According to the migration direction of the channels, the spatial configuration relationship of the sand bodies was formed and abandoned channels were identified. With abandoned channels as the boundaries and combined with the rhythmic characteristics of point bar sand bodies, the head and tail of the point bars were determined to divide the point bar range, and then each individual point bar sand body was identified from the plane and section. The internal characteristics of point bar sand bodies were analyzed in detail. By precisely identifying lateral accretion mudstone, the depositional stages of point bars were divided. Based on the quantitative calculation of the occurrence of lateral accretion mudstone by the method of twin wells, the width of the single lateral accretion layer was approximately 430 m. Through the comparison of horizontal well drilling, the calculated results were similar to the actual drilling results. By applying this method to guide the deployment of well K-4 X, good development effects were achieved. It was confirmed that this method has strong practical guiding significance in the identification and quantitative characterization of point bars in X block.

In order to ensure the safe and smooth operation of the gas storage and effectively evaluate the geologic body sealing capacity of the gas storage, the stability of the cap rocks and faults is evaluated. Taking Dagang Z gas storage as the research object, based on data such as geological gas reservoir characteristics, production dynamic characteristics, rock mechanics experiments, combined with the characteristics of alternating ground stress changes in the gas storage after multiple cycles of high-speed alternating injection and production, a four-dimensional dynamic geomechanics model is established to comprehensively evaluate the trap sealing capacity after 30 years of development and 20 injection and production cycles. The research results show that:①The ultimate bearing capacity of the geologic body cap of the Z gas storage is 48.8 MPa, the ultimate bearing capacity of controlling-trap T fault is 35.1 MPa, and the upper limit pore pressure of the Z gas storage operation is 31.5 MPa, which is within the safe range;②During the long term high-speed alternating injection and production operation of Z gas storage, the cap rocks, reservoirs and faults are not damaged, but geomechanical simulations show that individual risk points appeared on controlling-trap T fault, but it is still relatively safe at present;③It is recommended to carry out real-time dynamic monitoring of the geologic bodies of the Z gas storage based on the research of the four-dimensional geomechanical model, and combined with the actual dynamic monitoring data. Monitoring wells on the upper wall of the T fault risk points of the Z gas storage are deployed, strengthening injection and production dynamic monitoring and ensuring long-term safe and smooth operation of the gas storage.

The vertical characteristics of the logging curves of the lower target bed in Q₉ oil layer of Gulong shale in Daqing Oilfield are small,which make it difficult to track the drilling of horizontal wells. By optimizing and subdividing the core target bed,the logging curve characteristics are clarified,and a method of horizontal well guiding while drilling is formed. The average relative error of entering the target is 1.1‰,and the drilling rate of the core target bed has been increased to over 90%. Meanwhile,a post drilling evaluation method applicable to Gulong shale oil horizontal wells has been preliminary established,which effectively guides the fracturing design through geological subdivision of horizontal sections. The research results have been overall applied in the drilling and development of Gulong shale oil,and the zipper type integral fracturing of horizontal wells has achieved good stimulation effects.

Metamorphic buried hill is the key field of oil and gas exploration in Bohai Bay Basin. As a horst structure on the west side of the eastern depression of Liaohe Depression,the oil and gas distribution of Ciyutuo buried hill is controlled by the weathered crust structure and significant physical property differentiation. In order to clarify the cause of uneven distribution of oil and gas in Ciyutuo buried hill,the longitudinal structure division and characteristics of the weathering crust on the top of buried hill were studied by using core,thin section,well logging and analysis data,so as to analyze its evolutionary process and physical property distribution law and clarify the control effect of the weathering crust on hydrocarbon accumulation in the buried hill. The results show that the weathering crust of Ciyutuo buried hill lacks clay bands and weathered glutenite bands,and is vertically composed of leached zones and disintegration zones. The weathering crust thickness and physical properties differences control the formation of "up dip pinch out" traps,and the leached zone （permeability higher than 10 mD） is the dominant migration channel. Graded simulations of hydrocarbon generation intensity show that under high hydrocarbon generation intensity with 5×10⁶ t/km²,oil and gas can charge the disintegration zone （thickness higher than 12 m）. The results reveal the controlling effect of weathering crust on hydrocarbon accumulation in buried hill,and provide an important basis for deepening the understanding of reservoir-formation law and optimizing exploration deployment.