With the introduction of AI and big data technologies, the oil and gas exploration field has realized a paradigm shift in the drilling process from being experience-driven to data-driven. At the same time, geology-engineering integration services also have shifted from "drilling wells successfully" to "drilling wells quickly". However, the integration technology still remains at the optimization and improvement phase of the working mode and operation process. During drilling in complex formations, there are still technical problems such as limited penetration rate, low trajectory control accuracy, and lagging response to downhole risks, which restrict the further development of this field. AI technology provides a new path to break through the bottlenecks： Through dynamic Mechanical Specific Energy （MSE） modeling and real-time optimization, accurate mapping from formation characteristics to engineering parameters is achieved. With this as the core, an intelligent drilling optimization system driven by the three cores of "data, decision and execution" has been built to achieve full-process closed-loop optimization. It has been successfully applied in the on-site drilling construction process, verifying that this system can improve penetration rate, reduce non-production time, and effectively control the deviation of the wellbore trajectory. This study provides theoretical support for the development of the intelligent drilling optimization system, reveals the transformation of digital technology to the traditional drilling optimization working mode, and provides replicable solution at the engineering level.

To improve the precision of reservoir identification by mud logging in oil and gas exploration, a mud logging system based on infrared spectroscopy technology has been developed. The hardware of the system adopts a miniaturized and integrated design with a high-sensitivity infrared detector, realizes the comprehensive identification of gas spectral features through infrared spectroscopy scanning technology, and completes the rapid and automatic analysis of hydrocarbons in drilling fluid. The software of the system has functions such as remote data sharing, software mapping and data analysis, which is used to realize stratigraphic interpretation and evaluation. The field test shows that the infrared spectroscopy gas logging system can quickly find the show of gas and oil, and has obvious technical advantages in the evaluation of thin beds and fracture-type reservoirs. It also has the advantages of high precision, low error, rapid response and good repeatability. It can meet the needs of mud logging operations in different regions and effectively improve the accuracy of reservoir evaluation.

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.

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.

With the improvement of drilling technology,the drilling speed of drilling exploration has been greatly increased,especially in the offshore drilling platforms and shallow well drilling,the drilling time per meter is extremely small （generally 0.1-1.0 min/m）,while the delay time of the gas collection pipeline for mud logging samples is usually the range of 2-10 min. When a single pipe is connected or the pump is stopped for special reasons,the sand return depth in the mud logging acquisition software will stop updating. However,the gas corresponding to the sand return depth in the sample gas pipeline is still being analyzed by chromatograph. The result is that the gas logging data analyzed by the chromatograph cannot correspond to the lagged well depth,and the gas logging data is "lost". The amount of "lost" data is determined by the lag time of the gas pipeline and the drilling time. In order to ensure the complete collection of gas logging data,an automatic control device for mud logging sample gas collection has been developed. The device collects real-time drilling status through RS-232 serial communication,and uses a microcontroller control unit in the integrated circuit to control the electromagnetic valve on the automatic control device to switch the sample gas pipeline,achieving accurate analysis of the sample gas in the pipeline and avoiding the "loss" of gas logging data.

With the deepening of oil and gas exploration and development, the traditional gas logging interpretation methods mainly based on charts are unable to meet the evaluation needs of the relationships between the complex reservoirs and oil, gas and water. In recent years, the rapid development of big data analysis and machine learning has provided a new direction for gas logging interpretation. Based on gas logging interpretation data from multiple wells, data preprocessing and feature engineering methods are applied to process the gas logging data, and five common machine learning models （KNN, NB, SVM, MLP, LightGBM） are used for modeling interpretation,application,comparison and analysis. The results show that the comprehensive performance of SVM and LightGBM models is good with an average prediction accuracy of over 87%, which can meet the actual interpretation needs. The machine learning model solves the problems of the insufficient flexibility of the traditional interpretation charts and the difficulty of extracting deep information due to the dimensional limitations, and significantly improves the interpretation accuracy, which has the practical value of promotion and application.

Regarding the identification of fluid properties in low and ultra-low permeability reservoirs in Liu-2 and Liu-3 Members in Weixinan Sag,Beibuwan Basin,conventional logging techniques and interpretation methods are severely limited under the contamination of oil-based drilling fluid,resulting in insufficient accuracy of fluid property discrimination and difficulties in real-time decision making on site. Using the gas characteristic spectrum discriminant method,original absorption rate spectrum discriminant method,and oil and gas index quantitative discriminant method of the hydrocarbon phase state evaluation technology,the fluid properties of the low-permeability reservoirs in this block are analyzed,and the extended applications of this technology in fracture identification and oil and gas sources are discussed. The results show that the hydrocarbon phase state evaluation technology has played a unique advantage in oil and gas classification and reservoir water content identification. For the identification of fluid properties in more than 20 wells of various well types and reservoirs in different formations in Weixinan Sag,the coincidence rate of the comprehensive interpretation is over 90%. This method effectively solves the problem of fluid property identification caused by the dual factors of oil-based drilling fluid pollution and low-permeability reservoirs in Weixinan Sag,provides reliable technical support for offshore oil and gas field development and has significant value for popularization and application.

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.

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.

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.

Gulong shale mainly consists of large suites of clayey felsic shales with many pore types and complex pore structures,and its reservoir performance is the core in shale oil geological research,but conventional logging methods are difficult to effectively evaluate such micro-nano pores. To solve this problem, NMR technique is applied to geophysical logging to full-scale characterize the porosity and pore structure of shale reservoirs. By building the conversion relationship between NMR relaxation time （T₂） and rock pore diameter, the proportion of large pores in Gulong shale was characterized by the specific T₂ spectrum components to evaluate the shale reservoir performance quantitatively, systematically revealing the pore structure differences and distribution law of Gulong shale reservoirs. Based on the results of the reservoir performance evaluation,the target strata with large porosity and good pore structure were selected to optimize the horizontal well trajectory designs. The results show that with the changes of rock mineral compositions, there are differences in the vertical pore structures of Gulong shale reservoirs. Among them, the middle-lower part of Q₉ oil layer has the highest proportion of large pores and the best pore structures. The overall production of horizontal wells in the expanded test area,which is implemented by using this part as the core target window of horizontal wells,has been greatly improved. This technology will provide favourable support for the follow-up efficient development of Gulong shale oil.

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.

In the exploration of Pearl River Mouth Basin, a large amount of CO₂ gas was found, and its genesis is complex, covering organic origin, inorganic origin and mixed origin. The study on CO₂ formation mechanism in this area is of great significance to judge the source of oil and gas and the mode of accumulation. However, the CO₂ monitored during mud logging while drilling may originate from the added drilling fluid materials, which has a significant influence on CO₂ genesis study. Because CO₂ inherits the geochemical information of maternal materials during its formation, different ${{\delta }^{13}}{{C}_{C{{O}_{2}}}}$ can indicate different biological sources. Through the design of relevant experiments, the ${{\delta }^{13}}{{C}_{C{{O}_{2}}}}$ values of the drilling fluid materials are obtained. Compared with the ${{\delta }^{13}}{{C}_{C{{O}_{2}}}}$ values measured during mud logging while drilling process, the sources of CO₂ can be confirmed. The ${{\delta }^{13}}{{C}_{C{{O}_{2}}}}$ values in the drilling fluid materials from wells A and B are quite different from the ${{\delta }^{13}}{{C}_{C{{O}_{2}}}}$ values while drilling, which indicates that CO₂ originates from formation rather than the drilling fluid materials. According to this, it is confirmed that CO₂ in well A of Enping Sag is the organic origin of organic matter pyrolysis, and CO₂ in well B of Eastern Yangjiang Sag is the inorganic origin of mantle source. This study provides important geochemical basis for oil and gas exploration in Enping Sag and Eastern Yangjiang Sag.

Aiming at the problem of the low coincidence rate of the interpretation of the reservoir fluid properties in gas exploration wells in Ordos Basin, the key influencing factors of NMR logging technology were systematically analyzed. Based on core experimental data, a quantitative evaluation model centered on NMR porosity and the dynamic ratio of the initial state movable water saturation to the initial state irreducible water saturation was reconstructed, breaking through the excessive reliance on data quality by the traditional intuitive identification method of spectra. Field application shows that the model significantly improves the accuracy of reservoir water content discrimination by standardizing data acquisition process and establishing reservoir gradation and classification standards, and the interpretation coincidence rate increases from 79.23% to 85.32%. The research results confirm that the dynamic ratio parameter model can effectively characterize the fluid distribution characteristics of low-porosity and low-permeability reservoirs, thereby providing reliable technical support for the optimization of well completion test intervals and the establishment of reservoir stimulation schemes under complex geologic conditions, and has promotion value for the exploration and development of similar hydrocarbon reservoirs.

In order to solve the problem of accurate identification of fluids with different properties in complex reservoirs in oil and gas exploration,based on the application data of infrared spectrum technology in the Bohai Bay Basin,five sensitive wavelengths were optimized and four sets of key parameter combinations were screened by analyzing the spectral absorption efficiency curve characteristics of fluids with different properties. Through constructing the multiparameter fusion charts,the rapid identification and accurate evaluation of oil layers,high-GOR oil layers,gas layers,and oil-bearing water layers have been achieved. Validated by data of on-site testing while drilling in 6 wells,the interpretation coincidence rate of infrared spectrum technology reached 92.3%. This method not only improves the qualitative analysis ability of reservoir fluid,but also provides more efficient technical support for hydrocarbon reservoir exploration and development,and has important engineering application value.

In the field of geologic exploration, density logging curve is of great significance in determining reservoir porosity, identifying gas reservoirs, judging lithology, dividing oil-water interfaces, identifying fluid types, and improving inversion accuracy. However, in practical operation, logs may be lost or distorted due to instrument failures, data transmission errors or external interference. To solve this problem, this paper proposes a density logging curve reconstruction method based on Transformer-LSTM fusion model. This method utilizes Transformer′s self-attention mechanism to effectively capture the long-distance dependency relation in log data, and combines with the recursive characteristics of Long Short-Term Memory （LSTM） to significantly improve the reconstruction accuracy. By preprocessing, model construction and training of log data from Y zone of Ordos Basin, the performance is compared with bidirectional gated recurrent unit （BiGRU）, deep neural networks （DNN）, multiple regression analysis （Logistic）, temporal convolutional network （TCN） and Transformer model. The results show that Transformer-LSTM fusion model performs well in density logging curve reconstruction, especially in terms of reconstruction accuracy and generalization ability. The experimental results verify that the model is capable of reconstructing high-precision density curve data, providing reliable support for geologic exploration.

A large number of glutenite segments are developed in the northern actic region of Dongying Sag, which is a favorable place for hydrocarbon enrichment and plays an important role in oil and gas exploration. However, in recent years, no effective hydrocarbon shows have been found in many wells in Shengtuo area during the drilling process of glutenite body under the lower section of Es₄. To explain the cause of this anomaly, based on the theory of hydrocarbon accumulation, combined with tectonic evolution, sedimentary history and logging data, this paper analyzes the reservoir-forming control conditions of source rocks, reservoirs, caprocks and traps in the lower section of Es₄ in Tuoshen 3 block. It is clarified that the self-sourced hydrocarbon reservoirs are mainly developed in the block. Compared with the source rocks of the low position in the upper section of Es₄, the source rocks developed under the salt-gypsum formations in the lower section of Es₄ with poor oil-bearing property and small oil-generating potential, so it is difficult to provide oil source support. Under the depositional setting of deep and semi-deep lacustrine, the thick-bedded salt-gypsum formations deposited on the top of the glutenite body constitute a high quality caprocks, and the isolated and discontinuous reservoir bodies developed under it have poor physical properties. The oil and gas are mainly migrated to the traps for preservation through the transporting system composed of faults, sand bodies and unconformity surfaces, and the structural-lithologic trap and sedimentary evolution model jointly control the hydrocarbon accumulation in the block. The study provides an important reference for the exploration,identification, and the later productivity construction of glutenite body in the lower section of Es₄, Tuoshen 3 block.

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.

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 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.

The exploration targets of Bohai Oilfield are shifting towards oil reservoir zones with complex geologic conditions, resulting in a significant increase in the difficulty of oil-water layer interpretation and evaluation. The traditional comprehensive evaluation method combining mud logging and well logging technologies restricts the operation efficiency to a certain extent due to the hysteresis of well logging technology. Therefore, a quantitative calculation model of oil saturation based on geochemical logging was established. This model comprehensively considers the distribution laws of oil-gas-water three-phase flow in reservoir pores and the influence of petrophysical properties （crude oil density, reservoir porosity, matrix density, etc.） on oil saturation, providing a new angle of view and tool for accurate assessment of reservoir fluid properties and realizing the real-time evaluation of reservoir fluid properties. Verified by the data of the wells newly drilled in X block of Bohai Oilfield, the accuracy rate of model interpretation was 86.67%.The oil saturation calculation model can provide strong support for oil-gas exploration and development in Bohai Oilfield.

Aiming at the technical problem that it is difficult to quantitatively analyze the contamination degree of wireline formation test samples in oil-based drilling fluid environment due to the miscibility of crude oil and drilling fluid, this paper proposes a comprehensive quantitative evaluation method based on conventional fluid physical comparative analysis and saturated hydrocarbon gas chromatography component comparative analysis. Through the establishment of the sample density analysis chart and the gas chromatographic analysis chart, the calculation software of formation crude oil drilling fluid contamination proportion was developed, and the quantitative evaluation of the effects of oil-based drilling fluid on the contamination degree of the wireline formation test samples was realized. The method has been applied to 14 wells in Weixinan Sag of Beibu Gulf Basin. The analysis results show that the maximum absolute errors are within 5% compared with the laboratory sample analysis results and oil testing productivity analysis data. The field application results show that the method has high analytical accuracy and practicability, and can realize the rapid and accurate evaluation of oil-based drilling fluid contamination rate in wireline formation test samples.

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.

The identification of fluid properties in low-contrast reservoirs is a technical bottleneck in the field of oil-gas exploration and development, its core characteristics are manifested in the weak differences in resistivity between oil layers and water layers, which are difficult to effectively distinguish on conventional log response. In response to this problem, taking the shallow low-resistivity oil layers in Hanjiang Formation of Enping Sag and the Paleogene high-resistivity water layers in Lufeng Sag, Pearl River Basin as examples, a "3-axis linkage" mud logging evaluation technology system is constructed: gas logging identifies hydrocarbon anomalies, real-time fluid logging quantitatively characterizes hydrocarbon abundance and geochemical logging identifies the phase states of the fluids （oil or water layers）. On this basis, the multiparameter quantitative interpretation charts have been established, which effectively solve the evaluation difficulties in the reservoirs of thin interbedded layers and low-resistivity oil layers, and the accuracy of regional fluid property identification has been increased to more than 85%. In practice, well A 3H in Enping Sag has obtained a high-yield oil flow of 823 t/d, and in Lufeng Sag, the interfaces of high-resistivity water layers have been successfully identified, which make the identification accuracy of high-resistivity water layers with 55% of the traditional interpretation based on logging resistivity data increase to 82%, and provide a reliable technical support for the high efficiency development of the complex hydrocarbon reservoirs in South China Sea.

With the deepening of oil and gas exploration, it has become an inevitable trend to develop from middle-shallow to deep layers. In particular, major breakthroughs have been made in the deep exploration of the Permian in Mahu Sag and the Carboniferous in Shawan Sag, Junggar Basin, and the deep exploration has become an important replacement field for oil field reserve increase and production increase. However, in the Permian and Carboniferous strata, there are diverse rock types, complex compositions, fine drill cuttings, leading to difficulty in quickly identifying lithology, which restrict the efficiency deep oil and gas exploration. Therefore, X-ray diffraction mineral logging and Gamma spectrometry logging while drilling technologies have been introduced for research on the deep and mainly developed Permian and Carboniferous strata. Combined with thin section identification, the lithology identification charts can be established by dividing blocks and layering positions through the rock-mineral index model and the optimization of typical minerals. This provides a new method for rapid identification of lithology and precise horizon determination, guaranteeing drilling safety and further improving mud logging technology system. At present, a total of 13 wells have been applied, with the coincidence rate of over 82% for lithology identification. In the field of deep oil and gas exploration and development, the application effect is obvious.

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.

Liuheying-Daxinzhuang structural belts are second-level oil-bearing structural belts located at the southwestern end of the western zone in Langgu Sag, with low degree of exploration. Due to its complex structure and sparse survey grid, the hydrocarbon accumulation regularities remain unclear. Based on the data of well-seismic combination, actually drilled geology and analytic test, the hydrocarbon accumulation conditions and exploration potential are deeply analyzed. The results are obtained in four aspects. First, The Es₃^l dark mudstone is the dominant source rock beds and has good oil source conditions with a large thickness of 600-1 600 m, high organic matter abundance of TOC 0.64%-1.03%, and main kerogen type Ⅱ₂-Ⅲ. Second, As a whole, Es₃ reservoirs are dominated by medium-high porosity and low permeability, with the best physical properties in Es₃^m of Daxinzhuang arched structural belt, and the reservoir-cap rock assemblage in Es₃ is superior. Third, The structural belts are clamped between the two large oil-generating troughs of western Gu′an and southern Liuheying, the oil and gas enrichment is jointly controlled by the nose-like structural trap, the turbidite sand body distribution, and the dual effects of oil source fault transport and later tectonic uplift, forming the down generated up stored and side generated lateral stored reservoir-forming patterns. Fourth, two reservoir-forming patterns of ridge-type and toothbrush-shaped structures were constructed to reveal the banded enrichment regularity of oil and gas along the structural high parts and faults. G 8 trap and No.2 trap in northern L 1 were selected as the most favorable targets from 49 traps, with the total quantity of oil resources of over 500×10⁴ t and natural gas of nearly 40×10⁸ m³ predicted. The results provide theoretical guidance and technical support for the subsequent research and exploration of oil-bearing traps in the complex structural zones of Langgu Sag.

The Middle Indus Basin is located in the central part of the Indus Basin, which is a foreland basin developed from the passive continental margin. Previous research suggests that the factors controlling the formation of tight gas reservoirs in foreland basins are fault transport of oil and gas and fracture transformation of reservoirs, with oil and gas enriched in fracture developed zones near the faults. However, the drilling results in the local area are different from the previous research results. Not all faults in the area are enriched with oil and gas. Most of the wells successfully drilled in this area are distributed along NS-trending faults, and exploration near the NW-trending faults has not been broken through. Therefore, it is urgent to conduct more in-depth research on the differences in fault-controlled reservoirs, and explore tight gas reservoir formation models suitable for this area. Based on the understanding of regional geology and fine interpretation of seismic data, the characteristics and development stages of faults in M area have been summarized, with a focus on the structural evolution processes and stress conditions that give rise to these fault characteristics. This paper analyzes the sealing ability of these faults, and finally reveals fault controlling regulation on differential hydrocarbon accumulation in this area. The research provides a theoretical foundation for tight gas exploration in the Middle Indus Basin. The results indicate that NW-trending faults suffered compressive stress in Early Cretaceous epoch, leading to significant shale smearing and a certain sealing capability. The nearly NS-trending faults functioned as the main migration pathways for gas, controlling the hydrocarbon migration and accumulation. The tight sandstone reservoirs on both sides of these faults have been transformed by faults and fractures, and have great accumulation potential, which point out the way for the next exploration and development of the gas field.

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.

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.

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.

Pai 612 block of Chunfeng Oilfield is the first block to develop super-extra viscous crude oil reservoirs in western Junggar Basin. Currently,multi-cycle steam injection exacerbates the heterogeneity of the reservoirs,and there are development problems such as frequent inter-well steam channeling and uneven reserve production. In order to deepen the understanding of reservoir heterogeneity,it is urgent to carry out differential lithofacies study and geologic modeling of reservoirs. The reservoirs of Pai 612 block are mainly divided into high-quality sandstone facies and calcareous sandstone facies. On this basis,the seismic data analysis and horizontal well stratigraphic correlation were used to improve the accuracy of structural control,and the structural model was established. Combined with the lithofacies study and the analysis of core data and log information,the linear correspondence between the lithofacies and the gamma curve of horizontal wells was determined,and the lithofacies data of the horizontal wells was quantitatively calculated to establish a differential lithofacies model for the block. The vertical well attribute model was established by regressing interval transit time and physical properties based on the analyzing and rock sample testing data of the cored wells, and the horizontal well attribute model was established based on the correlation between shale content and physical properties. Finally,by comparing the static and dynamic characteristics of different lithofacies reservoirs,as well as analyzing the production capacity,the net to gross ratio of different lithofacies was determined,and the production of calcareous sandstone facies accounted for 66.7% of high-quality sandstone facies. The different lithofacies differentiation net to gross ratio model of the final completion lays the foundation for improving remaining oil recovery efficiency in the later stage.

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.

Mud logging and well logging data play an important role in reservoir fluid identification, especially during the drilling stage. The data volumes of mud logging and well logging data depend on the number of wells in the area, and the number of samples is relatively small in terms of big data dimensions of offshore oil and gas exploration, which limits the machine learning of reservoir fluid identification due to the small amount of labeled data and leads to overfitting and poor generalization ability issues. To address the above problems, this paper proposes a fluid identification method that combines semi-supervised learning （Self-Train） with Markov Chain Monte Carlo （MCMC）. First, train the neural network model using a small amount of labeled data. Second, combining semi-supervised self learning algorithms to generate machine labels （pseudo labels） for unlabeled data. Then, using MCMC method to randomly sample and quantify the uncertainty predicted by the model, machine labels with high confidence coefficient are selected to expand the high-quality training dataset. Finally, by combining the screened machine tag with the original label data, and adopting adaptive training method to adjust and use the neural network model that is established with labeled data, a reservoir fluid identification model is created for mud logging and well logging data suitable for few-shot conditions. The model validation for new drilling wells achieved a coincidence rate of over 85%, demonstrating well application results. The reservoir identification model established after screening machine tags using the MCMC method improved the accuracy and generalization ability of the fluid interpretation model while drilling, providing effective technical support for rapid identification of fluids while drilling at the well site.

The source direction, sedimentary facies evolution history and distribution law of oil-bearing series of Shahejie Formation in Wen'an slope, Jizhong Depression, are still unclear. Based on core, well logging, seismic and other geologic information, the provenance system and sedimentary facies characteristics of Shahejie Formation were discussed in depth through paleogeomorphological restoration method and heavy mineral Q type clustering procedure. The results indicate that the sedimentation of Shahejie Formation in Wen′an slope has multi-source characteristics, and the provenance mainly comes from the northwest of Niutuozhen uplift and the southeastern Wen′an slope. Two major source areas developed multiple transport pathways. Sediments have developed several graded sand bodies along the slope topography. Influenced by the steep western and wide-flat eastern paleogeomorphological pattern, Shahejie Formation mainly developed three sedimentary facies during its sedimentary period： fan delta, braided river delta and lake. During Member 3 of Shahejie Formation sedimentary stage, five sedimentary subfacies were mainly developed in the study area： fan delta plain and front, braided river delta plain and front and shore-shallow lacus. Multiple delta lobes were formed along the subaqueous distributary channels. During Member 2 of Shahejie Formation sedimentary stage, the northwest of the study area mainly developed shore-shallow lacustrine mud microfacies, while the southeast mainly developed two sedimentary subfacies of braided river delta plain and front. During Member 1 of Shahejie Formation sedimentary stage, the northwest of the study area mainly developed two sedimentary subfacies of fan delta plain and front. The southeast mainly developed braided river delta plain, with a small amount of braided river delta front sedimentary subfacies. The study results can provide theoretical basis and guidance for the further refined exploration and development of hydrocarbon resources in Shahejie Formation of Wen′an slope in Jizhong Depression.

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.

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.

To reduce the workload of data acquisition personnel on the drilling site,fully reuse the collected drilling data,and achieve the effect of "one party entry,multiple parties sharing" of data,data changes are perceived through database triggers,and data heterogeneous synchronization is realized with the dynamic configuration of model transformation rules. The use of message queue to decouple the functions of data change capture and data synchronization improves system performance,ultimately leading to the research and development of a heterogeneous synchronization system for drilling data. Since the system went online,a total of 2.8×10⁸ pieces of data have been synchronized,with an average of 61.14×10⁴ pieces of real-time synchronized data per day,greatly reducing the burden of data filling in and submitting for on-site personnel,making data sharing more secure and timely,and realizing unified management of data synchronization. This system has produced a marked effect in breaking down data barriers,eliminating data silos,improving data utilization rate,ensuring data consistency,and promoting cross-disciplinary collaboration.It provides strong data support for the analysis and decision-making activities of enterprise managers.

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 fully understand the hydrocarbon accumulation process in Nanpu No.3 structural belt, and improve the effectiveness of oil and gas exploration, based on the data of geology and geochemistry, and using the technique of petroliferous basin numerical simulation, this paper reconstructs hydrocarbon-generating and hydrocarbon-expulsing histories, and discusses the matching relation of hydrocarbon accumulation on the basis of the systematic analysis of the source rock. The results show that there are three sets of source rock,including Es₃, Es₁ and Ed₃ in the study area,and the main types of organic matter are Ⅱ with high organic matter abundance. The Es₃ source rock have high hydrocarbon-generating and hydrocarbon-expulsing intensity at the stage of maturity and high maturity, and the mass process of hydrocarbon generation and expulsion happened from the end of Dongying sedimentation to the middle of Minghuazhen sedimentation. The Es₁ and Ed₃ source rocks have medium hydrocarbon-generating and hydrocarbon-expulsing intensity at the stage of maturity, and the main process of hydrocarbon generation and expulsion happened from the middle Minghuazhen sedimentation to present. The trap forming epoch matches well with generation, expulsion, migration and accumulation of hydrocarbon. The deep and middle-deep oil and gas exploration in the study area should take the source rocks of the Es₃ as the oil source, and the middle-shallow oil and gas exploration should take the source rocks of Es₁+Ed₃ as the oil source. The favorable exploration objects include structural and lithologic traps that are adjacent to Caofeidian sub-sag and have faults vertically connecting the source rocks and reservoirs.