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.

Accurate identification of site lithology plays an important role in oil and gas exploration and development. As the difficulty of exploration increases, the difficulty of lithology identification on site also increases accordingly. An intelligent identification method of lithology based on data while drilling is proposed to solve the problem of on-site stratigraphic lithology identification while drilling. This method analyzes the formation elements and parameters while drilling, extracts the eigenvectors, establishes the multiple-feature collection library of different lithology, and realizes the lithology intelligent identification based on data while drilling by using the generalized regression neural network model of the Max-Min Ant System optimization algorithm.This method is applied to actual lithology identification while drilling, and the MMAS-GRNN model constructed from non-feature extraction data and feature extraction fusion data is compared.The experimental results show that the accuracy rate of stratigraphic lithology identification of MMAS-GRNN model based on multi-source information feature extraction fusion data reaches 90.71%, which is 4.76% higher than that of non-feature extraction data model, showing the superiority of multi-source data after feature extraction fusion in stratigraphic lithology identification effect.

With the continuous breakthroughs in shale oil and gas exploration and development, the "Well Factory" model came into being in order to meet the needs of the shale oil and gas drilling factory construction model and the integrated construction of drilling, well logging, mud logging, and directional well. However,in many aspects such as well site construction, rear management and data application, the profession of drilling, well logging, mud logging, and directional well operates independently and lacks coordination and management methods. Therefore, business operations are scattered, software is difficult to integrate, data is difficult to share, and there is a lack of a unified comprehensive application platform to meet the need of "Well Factory" model. With the help of the "Well Factory" model, a cross-professional, cross-regional, and cross-organizational integrated decision support platform has been built, which can realize the organic fusion of various professional technologies, real-time sharing, and collaborative linkage among multiple parties. The platform meets the needs of integrated geological engineering construction and has reference significance for the construction and development of intelligent oil and gas fields.

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.

The drilling fluid level in the buffer tank at the mud logging site often fluctuates up and down with the changes of pump displacement and bottom-hole complex situations, and the influence of some human factors. In order to stabilize degassing, the degasser needs to be manually regulated according to the changes of drilling fluid level. Otherwise, if the drilling fluid level is too high, it may cause the pumping drilling fluid to block the gas pipeline and burn the motor.If the drilling fluid level is too low to degas the drilling fluid, resulting in the loss of gas logging data. In order to save manpower and ensure the accuracy and timeliness of gas logging data, the full automatic level self-regulating degasser has been researched and developed, which can measure the level height through the ultrasonic liquid level sensor, then drive the motor to regulate the liquid intake height of the degasser up and down, and automatically deal with the complex situations such as level heave and excessive drilling fluid bubbles in the buffer tank. Compared with the traditional degassers, the full automatic level self-regulating degasser changes the regulation drive mode, realizes automatic regulation for the liquid intake height of the degasser, thereby reducing labor intensity, improving equipment operation reliability and inherent safety, and enhancing the quality of gas logging data.

With the organizational restructuring of China Petroleum and vigorous widespread of teams of private petroleum enterprises,mud logging operations are currently undertaken by personnel without a geology（logging） background or young engineers,who lack of work experience and complete professional knowledge,and this leads to an increase in misoperations,false alarms and omissions,which results in growing risks to drilling well-control and brings a threat to production safety that cannot be ignored. An intelligent mud logging platform is proposed focused on MapReduce technology,which includes a series of core functional modules such as automatic generation of mud logging assignment, real-time warning of geological anomalies and comprehensive geological assessment. The construction of these functional modules has greatly improved the intelligent level of logging operations. After being applied in 98 mud logging teams and over 700 wells in the Chuanyu and Changqing regions,the digital mud logging operation model has effectively reduced misjudgments and oversights and provided strong technological support and safety assurance for improving drilling speed, efficiency and quality.

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.

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.

ZY 1 is a risk exploratory well in Nanyang Depression aiming to drill matrix shale oil. The original research believed that the sub-depression where Well ZY 1 is located is the most favorable area for matrix shale oil exploration. It is predicted that Well ZY 1 will drill into four sets of high-quality shale layers, but finally only drill into a relatively high-quality shale layer with a thickness of 85.0 meter of the strata of upper E₂h₂Ⅲ, while the strata of middle E₂h₂Ⅲ and E₂h₃Ⅱ drill into thick sandstone layers, which is quite different from the original prediction. In the absence of multi-well element data comparison, by analyzing the content changes of vertical easily migrating elements and argillaceous rock elements, combined with core logging data and regional geological data, the reason for the large difference between actual drilling and original prediction has been found out. The strata drilled by the well comes from two sources： the source of middle E₂h₂Ⅱ and upper E₂h₂Ⅲ strata comes from the northern delta, which is consistent with the original prediction; the source of middle E₂h₂Ⅲ and upper E₂h₃Ⅱ strata comes from the small sand body of the fault near the southern boundary. The impact of the actual drilling results of Well ZY 1 on oil and gas exploration is as follows： on the one hand, the area of source rocks has decreased, which has affected the calculation and evaluation of resources amount; on the other hand, it has provided new exploration areas. Based on element logging data and other exploration results, corresponding suggestions for oil and gas exploration in this area are put forward.

Drilling engineering data is of great value to drilling enterprises, and the implementation of digital transformation strategies in enterprises puts higher demands on data quality. However, due to multiple factors such as system planning, management requirements, and personnel operation levels, drilling enterprises often encounter problems such as low data quality, multiple sources of data, and time-lagged data in the process of oil exploration and development. In response to these problems, this paper summarizes and analyzes the types and causes of the problems, proposes a data governance plan suitable for drilling enterprises, combines the concept of data life cycle management with the data governance process, and designs technical and management measures focusing on four aspects： on-site data acquisition, data verification, assessment supervision, and data sharing. It elaborates on the specific implementation content of software upgrades at the acquisition software, development of web-based verification functions, and development of data synchronization and interface services. Meanwhile, it introduces the achievements made in drilling engineering data governance work. The implementation of the data governance plan not only meets the needs of drilling enterprises in production management, but also lays a foundation for the construction of fupper analysis and early warning applications.

Rapid and accurate prediction of crude oil density can directly support reserve calculation,operation plan formulation guidance,and exploration decision-making during the drilling process. Differences in reservoir bury depth,thermal evolution of hydrocarbon sources,and migration preservation conditions in the Zhu I Depression in the Pearl River Mouth Basin lead to large differences in crude oil density. Therefore,quantitative prediction of crude oil density cannot be achieved on the operation site,which brings a series of challenges to exploration operation and production plan decision-making. Based on the 3D quantitative fluorescence spectrum and laboratory crude oil density,combined with the regional oil qualitative classification standards,this paper uses the spectrum segmentation method to determine the proportion of different oil components. Then,correlation analysis is carried out with the crude oil density in the laboratory,and a quantitative calculation model of crude oil density based on 3D quantitative fluorescence logging data is constructed,which finally realizes real-time and quantitative prediction of crude oil density during the drilling process. Quantitative prediction of crude oil density is carried out in 9 wells in different target areas of the Zhu I Depression and finds that the relative error rate of crude oil density between the prediction and the measured results dose not exceed 2%,confirming that this method has good application prospects.

In view of mud logging enterprises' production and operation still using the traditional management modes such as paper documents and Excel tables,there are problems such as file preservation difficulties,limited functions,and inconvenience in cross-specialty statistics,the research on the establishment and application of an integrated management system for production and operation is carried out.In the process of building an integrated management system for production and operation,after in-depth analysis of the management and operation requirements of various departments of the companies,the hierarchical & micro-service architecture and frontier techniques were used to realize efficient data integration,processes optimization and intelligent decision-making. The application of this system can significantly improve management efficiency,reduce costs,and effectively promote digital management innovation in mud logging enterprises.

As exploration and development progress, deep coal-rock gas has gradually become one of the main targets for exploration. The deep coal-rock gas in the Wumaying coal accumulation belt of the Huanghua Depression may become an important region for sustaining production capacity in the Dagang Oilfield in the future. However, there is no existing experience in mud logging technology for coal-rock exploration in this region, the evaluation of mud logging while drilling is still blind area. Therefore, by analyzing the data of the multiple mud logging techniques of the Shanxi Formation and Taiyuan Formation coal measure strata from 7 wells in the Wumaying coal accumulation belt of Huanghua Depression, and summarizing the technical characteristics, the method of evaluation while drilling for coal-rock quality, gas bearing quality, characteristics of source rocks and fluorescence was initially formed. The method is well characterized in the comprehensive evaluation of Carboniferous-Permian coal measure strata in the study region, which provides favorable geological basis for the next exploration and deployment of deep coal-rock gas in Huanghua Depression.

Adhesive suction and sand settling are the common and frequent accidents for drill pipe sticking. The main reason for such accidents is that after the circulation is stopped or the drilling fluid is static, the drill tools are close to the borehole wall and lost the drilling fluid lubrication, and the horizontal positive pressure of the liquid column squeezes the drill tools to the borehole wall and compresses them tightly, resulting in the drill tools to tightly adhere to the borehole wall and bond with the mud cake. At the same time, the cuttings sinks, wrapping and plugging the down-hole drilling tools. A set of anti-sticking device with rotating circulation at the wellhead was developed by using the three-way technology of cycle seal, SIT function merging and rotation principle of high pressure washing pipe, which was used in 29 wells of Tuha,Santanghu and other oil and gas fields. When the drilling lifting system, rotating system or drilling fluid circulation system fails, the rotating circulation anti-sticking device is installed to realize the function of rotating drill tools and independent circulation, solving the problem of ineffective prevention of drill pipe sticking accidents of adhesive suction and sand settling caused by drilling lifting system, rotating system or drilling fluid circulation system failures in drilling sites. It provides technical support for optimal fast drilling and safe drilling.

As mud logging technology advances, carbon isotope logging has emerged as a prevalent technique in oil and gas exploration. The carbon isotope logging carried out around the shale oil zone in Weixinan Sag aims to effectively assess the maturity and origin of shale oil and gas in different horizons. Carbon isotope logging is used to obtain the isotopic composition of drilling fluid gas, and the carbon isotope logging characteristics from exploration wells at diverse structural positions are compared and analyzed. Meanwhile, by monitoring the isotopic fractionation characteristics of the cuttings headspace gas and volume changes in gas released from cuttings, the pore abundance and the characteristics of oil-gas potential for the shale are assessed. The carbon isotopes being a heavy trend within intercalated beds and interbeds for the oil shale in Weixinan Sag could be attributed to the charging of hydrocarbon generation products from deeply buried and highly evolved oil shale. The above results have identified the favorable reservoir horizons for oil and gas in Weixinan of Beibu Bay Basin, providing practical guidance for the deployment of follow-up oil and gas exploration.

As the first underground gas storage built and put into commercial operation in China, X gas storage of Dagang Oilfield has so far been safely operated for 24 injection and production cycles. In view of the problems exposed during the initial operation of the gas storage, such as poor capacity, production effects, and slow working gas growth rate, adaptability demonstration and optimization adjustment are carried out on the injection-production pattern and structure, operation mode and operating pressure, thus enhancing the gas storage and single well injection and gas production capabilities as well as liquid carrying and drainage capabilities. The expansion effect has been continuously improved, and the peak shaving capacity of the gas storage has increased by 1.17×10⁸ m³, with an increase of 24.2%. These provide mature technical means and practical experience that can be used for optimizing the operation and management of the same type of underground gas storage, and improving their peak shaving capabilities, which have important reference significance for the development of underground gas storage operation and management.

In the oil & gas exploration and development field,the detection of helium in the strata mainly relies on gas logging technology. However,during the process of drilling fluid returning to the ground through the annulus,gases such as helium that are not easily soluble in drilling fluid,will rise to the ground along with the drilling fluid and escape directly into the atmosphere through the liquid surface as the temperature,pressure and other environmental conditions change. At the same time,the existing electric degassing device is installed far away from the drilling fluid outlet,which cannot collect the helium escaping from the drilling fluid outlet pipe,thus affecting the reliability of helium detection. To this end,an anti-escape helium collecting device is designed and developed,which consists of a gas collecting chamber,floating buoys,a fixing device,an anti-escape gas replenishment pipe,a gas collecting pipe,a handle,etc. It is fixed at the outlet position of the drilling fluid line in the drilling fluid ditch. Its anti-escape gas replenishment pipe is directly connected with the drilling fluid outlet pipe,which can replenish the helium escaping from the drilling fluid to the gas collecting chamber,thereby being convenient to collect the gas in the drilling fluid in time,reduce the helium escaping,and effectively improve the reliability of helium detection.The device has the advantages of simple structure,low processing cost and convenient use. It is suitable for collecting helium in the outlet drilling fluid at the petroleum exploration sites,convenient for timely acquisition of helium content in drilling fluid,and improves the reliability and effectiveness of helium gas reservoir exploration.

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.

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.

As one of the unconventional energy sources,shale oil is important in increasing reserves and production. However,due to the difficulty in mining shale oil and the high construction cost,it is necessary to clarify the shale oil enrichment factors in order to achieve accurate positioning and effective development. Based on the shale layers of the Es₃ of Qibei subsag in Qikou Sag of the Bohai Bay Basin,comparative analysis of organic matter and occluded hydrocarbons of different lithofacies types is carried out,and the lithofacies types containing oil and gas with industrial value are clarified. By establishing the intersection relationship between mineral composition and free hydrocarbons,and analyzing the correlation between the number of fractures and laminae,the main controlling factors in the shale oil occurrence space are clarified. Research shows that the laminated shale and bedded mud shale are the main enriched lithofacies of shale oil in Shahejie Formation of the area,with good pore structure,high organic carbon content,high density of bedding fractures,and high occluded and free hydrocarbon content,which has production and development advantages. The study shows that lithofacies type,organic matter type and abundance,thermal evolution degree,rock minerals composition,and the number of laminae are the main factors affecting the enrichment and high yield of shale oil.

Accurate prediction of the productivity of shale gas wells is of crucial importance for the efficient development of shale gas. However,complex geological and engineering factors make production prediction a difficult problem in gas field development. This paper aims to establish harmonic decline and hyperbolic decline models to predict shale gas well early production by deeply studying the adsorption characteristics and seepage mechanism of shale gas,systematically monitoring the methane carbon isotope characteristics of natural gas samples from shale gas production wells,and combining the production historical data and production decline characteristics. Monitoring data shows that the methane carbon isotope of the production gas in shale gas wells continuously becomes lighter in the early stage,and becomes heavier after the implementation of stimulation measures. Moreover, after the daily production and the methane carbon isotope value reach their maximum simultaneously, the methane carbon isotope value begins to become lighter again, which may be the result of intensified separation due to diffusion effects after the production of adsorbed gas. Research shows that there is a good corresponding relationship between the change of methane carbon isotope in production gas and the change of gas production rate. Combined with production reality,the productivity prediction models of hyperbolic decline in the early stage and exponential decline in the later stage are adopted to make the predicted results more accurate. Through accurate dynamic monitoring of productivity and reserve estimate, shale gas development can be effectively guided.

Carbon isotope logging technology is widely used in oil exploration realm,especially in unconventional oil and gas exploration. To meet the large-scale exploration and development needs of shale oil and gas,DQL-T carbon isotope logging while drilling apparatus has been developed. It is based on chromatography coupled with mid-infrared quantum cascade laser and uses laser absorption spectrum technology,which is a gas detection technology with high detection performance,strong antijamming ability,and low usage cost. The isotopic values of carbon compounds can be detected quickly by the absorption characteristic peaks of the molecular bond of ¹²C-O or ¹³C-O on laser spectrum. The C₁-C₃ components of drilling fluid gas or cuttings headspace gas are separated and enter the oxidation pond,and the CO₂ generated by oxidation enters the mid-infrared laser spectrum measurement module for carbon isotope measurement. Through the research of "compact-linear" laser measurement module,superminiature volume gas absorption cavity and other techniques,the purpose of overall equipment miniaturization is achieved. The multistage temperature control technique is used to make the spectral core temperature fluctuation in the drilling environment less than 0.02 ℃,and the change characteristics of carbon isotope of drilling fluid gas and cuttings headspace gas can be measured in real time at the well site. The carbon isotope logging analysis of well X in an oil field shows that DQL-T carbon isotope logging while drilling apparatus can quickly measure carbon isotope and is suitable for the harsh environment in the field. Analysis suggests that the reservoirs with high δ¹³C_1-7 fractionation and moderate outgassing amount of the headspace gas have the high enrichment degree of the hydrocarbon accumulation,large occurrence pressure and relatively good physical properties,which can be used as the key reconstruction intervals.

The depositional environment of Chang 7 Member of the Triassic Yanchang Formation in Ordos Basin is mainly semi-deep and deep lacustrine facies,in which the deep water gravity flow deposition exists widely. In-depth analysis of these depositional characteristics and their spatial distribution regularities is of great significance for guiding oil and gas exploration. Based on Chang 7 Member in the southwest of Ordos Basin,the specific types and reservoir characteristics of deep water gravity flow deposition in this interval are clarified by means of fine core description,log data analysis and laboratory microscopic observation of cored wells. The sedimentary microfacies of deep water gravity flow in Chang 7 Member mainly include three typical types： sliding-slumping,sandy debris flow and turbidity current,which can be subdivided into eight types of lithofacies combinations. According to the well logging data,Chang 7 Member is divided into six types of representative electrofacies combinations. In terms of reservoir sand bodies,the sandy clastic flow and turbidity current deposits are dominant,and the sliding-slumping deposits are secondary,but they cannot be ignored. These reservoir sand bodies generally have low maturity,complex pore throat structure and poor physical properties. Different types of diagenesis show significant differences in the transformation effects on reservoir pores. This finding is of great significance for understanding the reservoir performance and evolution of deep water gravity flow deposition.

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.

In order to deepen the exploration of sweet spot identification methods and further improve the role of mud logging technology in shale oil exploration, according to the geological characteristics of Chang 7 shale oil in the Ordos Basin, research is carried out on the 100% coverage rate of gas logging technology, the hydrocarbon gases in the wellbore and the influencing factors of infrared spectrum logging are fully analyzed. On the basis of statistics on infrared spectrum logging data collected of Chang 7 shale oil in recent years, first, mathematical methods are used to clean the on-site collected data one after another, and then the oil and gas content in the broken debris in the wellbore is gradually calculated through diffusion gas correction and dilution coefficient correction formulas to represent the information of the real reservoir in the formation. Finally, an infrared spectral correction method suitable for Chang 7 shale oil horizontal wells is established, the wellbore environment correction is completed, and the infrared spectral data is standardized. From the perspective of application results, the revised total hydrocarbon data can more truly reflect the oil and gas information of the reservoirs and has good practical value.

In view of the low coincidence rate of reservoir interpretation and evaluation caused by the complex fluid properties and the influence of oil-based drilling fluid on field data in Xihu Depression, based on in-depth excavation of geochemical light hydrocarbon spectrogram and data, the complex fluid identification methods based on light hydrocarbon spectrogram shape and derived sensitive parameters are established, and have been verified by application. The results are obtained in three aspects. First, light oil layers and condensate gas layers can be identified based on the differences in light hydrocarbon spectrogram shapes. The former shows that the C₁-C₉ components of normal alkanes are relatively complete, and some isoalkanes, cycloalkanes, and aromatic hydrocarbons have complete and higher peaks. The latter shows that the normal alkanes after C₅ are missing, the detection range for the content of isoalkanes, cycloalkanes, and aromatic hydrocarbons is less, and the peaks are incomplete and the peak values are low. Second, by optimizing I_g（gas index）, I_o（oil index）, ∑（C₁-C₅）（gas-bearing index） and ∑（nC₆-nC₈）（oil-bearing index） that reflect the differences in light hydrocarbon detection components between light oil layers and condensate gas layers, the oil and gas identification chart has been established, which can effectively distinguish light oil layers and condensate gas layers. Third, based on the differences in solubility of different hydrocarbon components in water, the light hydrocarbon parameters of benzene, toluene, cyclohexane, and methylcyclohexane are optimized to establish a water content evaluation chart, which can determine the water content of the reservoirs. The methods are applied to the complex fluid evaluation while drilling of reservoirs in Xihu Depression, and the interpretation coincidence rate can reach more than 88%, which has good prospects for popularization and application.

In order to deeply understand the geological characteristics and reservoir characteristics of He 8 Member reservoirs from the Upper Paleozoic in Su 49 block,a systematic study of the reservoirs of it has been carried out from the perspectives of petrologic characteristics,pore types,pore-throat characteristics,and diagenesis by using core observation descriptions,casting thin sections,scanning electron microscope, cathodeluminescence and other experimental analysis data. The results show that the main rock types in He 8 Member reservoirs are lithic quartz sandstone and quartz sandstone,and the reservoir clast composition is mainly quartz（including quartz and flint）,followed by cuttings components,and there are some trace amounts of feldspar particles in some areas. The pore type in the study area is secondary pore,and the primary intergranular pore occupies a secondary position,and mainly characterized by the development of small pore throats. The lower sub-member of He 8 Member has good physical properties,with an average porosity of 8.15% and an average permeability of 0.58 mD. The physical properties of the upper sub-member of He 8 Member are second,indicating that the reservoirs of He 8 Member in the study area belong to tight ultra-low permeability sandstone reservoirs. The main diagenesis in He 8 Member includes compaction,cementation,and dissolution,of which the dissolution-formed kaolinite intercrystal pores and dissolution pores have a significant improvement effect on the reservoir physical properties. Micro-fractures have greatly improved the physical properties of reservoirs in the central and eastern parts of the block. The results of this study will help us better understand the natural gas storage rule in the area,provide scientific basis for reservoir stimulation and efficient development,and thus support the productivity construction and efficient development of the block.

Wellblock B of Huaqing area is located in the southwest of Ordos Basin. Chang 6₃ reservoir is the main horizon of this wellblock, and its sedimentary environment is gravity flow sedimentary system. With the continuous deepening of development in wellblock B, the development contradictions have gradually become prominent. The reservoirs are highly heterogeneous and the connectivity of sand bodies is poor, resulting in poor waterflood development effect and large productivity decline. Therefore, the sedimentary characteristics of gravity flow in this area were studied, and their impacts on oil and gas development were analyzed in combination with dynamic development data. Chang 6₃ reservoir in wellblock B is divided into six layers from top to bottom： Chang 6₃^1-1, Chang 6₃^1-2, Chang 6₃^2-1, Chang 6₃^2-2, Chang 6₃^3-1, and Chang 6₃^3-2. The characteristics of sedimentary petrology and log facies analysis in the study area show parallel bedding, mud boulder, flame structure, flute cast and other sedimentary structures on the cores. Chang 6 reservoir consists of lacustrine and turbidite deposit. The sedimentary microfacies are divided into four types： turbidite channel, turbidite channel flank, semi-deep lacustrine mud, and inter-turbidite channel. The sedimentary microfacies plane analysis shows that the sedimentary evolution of each Chang 6₃ layer is a process of water transgression to water recession. In terms of oil and gas waterflood development,because the sand bodies are controlled by sedimentary microfacies, the connectivity is good and the waterflood development effect is good for the reservoirs of the same stage.The sand body end-to-end connectivity in different stages is poor, and the effectiveness of waterflood development is poor. The study results can provide geological basis for oil and gas waterflood development in Huaqing area.

For the ultra-low-permeability oil reservoirs, water flooding technology is mainly used in conjunction with single well fracturing to improve the development effect. However, in the reservoir development practice, there are some problems, such as low efficiency of single well fracturing measures, poor effect of single sand body stimulation and inability to establish effective driving system between oil and water wells. Therefore, taking the ultra-low-permeability oil reservoirs in the X block of Songliao Basin as examples, the limit driving well spacing of the ultra-low-permeability reservoirs is calculated based on reservoir engineering method. At the same time, combined with the distribution law of sand bodies and remaining oil in the study area, the precise fracturing and stimulation scheme of single sand bodies in ultra-low-permeability oil reservoirs is formulated to ensure that the start-up coefficient between oil and water wells reaches the maximum after fracturing and stimulation, so as to avoid the problems of water breakthrough caused by excessive fracturing scale. And during the oil well fracturing stage, crosswell microseismic monitoring technology is used to track and monitor the scale of fracturing and stimulation of single sand bodies in ultra-low-permeability oil reservoirs. The fracturing scale is controlled by real-time adjusting the fracturing fluid displacement to ensure the precision of the fracturing scale. It is found that for types Ⅲ and Ⅳ reservoirs with the mean permeabilities of 6.5 mD and 3 mD in the study area, after well pattern infilling and single sand body precise fracture network fracturing by single sand body precise fracturing and stimulation technology, the single sand body start-up coefficient of the oil reservoirs and the production after oil well fracturing are significantly increased, indicating that an effective driving system has been established for the single sand bodies in the block, and the remaining oil potential tapping effect is significant.

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.

As one of the key secondary oil-bearing structural belts in the Langgu Sag, Jiuzhou slope belt has not made any new progress in exploration in recent years, with a relatively low level of exploration but abundant remaining resources. Aiming at the problems of unclear understanding of shallow structural features, difficult to accurately control the high points of lithologic trap and insufficient understanding of oil and gas enrichment rules for shallow Jiuzhou slope belt, this paper carried out a comprehensive geological study, and reshaped the regional target tectonic framework through multi-dimensional fault analysis. At the same time, a new accumulation pattern was constructed by evaluating sources-reservoir-cap assemblages, the type of trap, and the coupling development of reservoir sand body and structure and other aspects. The results show that the upper part of the upper sub-member of Sha-3 member in shallow Jiuzhou slope belt is mainly a structural reservoir, and lateral blocking is crucial to its hydrocarbon accumulation. The middle and lower parts of the upper sub-member of Sha-3 member to middle sub-member of Sha-3 member in middle-shallow Jiuzhou slope belt are mainly structural-lithologic reservoirs or lithologic reservoirs, and the development degree and the distribution characteristics of the reservoirs are the key factors for its hydrocarbon accumulation. Based on the comprehensive evaluation, two favorable targets, structural-lithologic trap in wellblock ZH 22 and structural-lithologic trap in southern part of wellblock X 5, were optimized, the resources quantity of the traps was predicted to reach 1 062.1×10⁴ t, both of which could be used to explore multi-layer targets with shallow burial, laying a solid foundation for the new breakthroughs in oil and gas and scale discovery of the reserves in this area.

In recent years, the importance of engineering sweet spots has become increasingly prominent, but the development of tight oil still focuses on geological sweet spots, which greatly limits the recoverable areas of oil reservoirs. Even though the concept of engineering sweet spots is considered in the development of tight oil, how to organically combine geological sweet spots with engineering sweet spots and conduct integrated evaluation is still a difficult problem. In order to evaluate the geological and engineering double sweet spots of tight oil, an indicator system including geological and engineering double sweet spot evaluation indices is first constructed. Then, the analytic hierarchy process is applied to determining the weight of each indicator in the indicator system and calculating the evaluation indices of the geological and engineering double sweet spots based on the indicator weights. Taking Jilin Oilfield as an application example, this paper presents how to use analytic hierarchy process to construct the evaluation indices of the geological and engineering double sweet spots for the target beds corresponding to each well position. By drawing the evaluation index plans of geological sweet spots, engineering sweet spots and geological and engineering double sweet spots, the new recoverable areas for sweet spots are found. At the same time, this paper introduces how to construct and calculate the evaluation indices of the geological and engineering double sweet spots for the tight oil horizontal wells, and presents the prominent role of the evaluation indices of the geological and engineering double sweet spots on regulating the well track during drilling and effectively tracing the oil layer sweet spots with the example. The actual drilling application validations at the well site show that the evaluation indices of tight oil geological and engineering double sweet spots based on the analytic hierarchy process can provide comprehensive and accurate guidance for oil & gas exploration and development, proving their practicability and effectiveness in geological and engineering evaluation.

To investigate the reasons for the production differences between the eastern and western Jurassic hydrocarbon reservoirs and explore the main control factors affecting single well productivity in the southern area of Ansai Oilfield, various methods such as well logging, core test analysis, high-pressure physical property testing of crude oil, and 3D seismic inversion were comprehensively applied to systematically study the effects of sedimentary facies, reservoir physical properties, clay minerals, oil properties, and formation pressure on productivity. The productivity difference between the eastern and western Jurassic hydrocarbon reservoirs in the southern area of Ansai Oilfield is mainly affected by the oil properties and formation pressure, with regional variations in crude oil density and viscosity being key factors. In addition, the direction of production increase technology for the eastern high viscosity and low pressure reservoirs has been proposed. The results point out the direction for the effective development and production and the measures of tapping potential for the Jurassic hydrocarbon reservoirs in Ansai Oilfield, and also provide valuable experiences for the progressive development of similar hydrocarbon reservoirs.

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.

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.

Mud logging data contains rich geologic information of hydrocarbon reservoirs,including reservoir characteristics,oil-bearing abundance,fluid properties,productivity status,etc. However,the accuracy and reliability of traditional mud logging interpretation and evaluation methods are greatly affected by human factors,making them difficult to meet the needs of quantitative and accurate evaluation. Based on the statistical multiple linear regression model and entropy method,a comprehensive analytic research was conducted on gas logging,element logging,rock-mineral logging and geochemical logging data. The reservoir physical property index（M_i） and oil-bearing abundance comprehensive evaluation score（F_i）were established,and a quantitative evaluation chart and criteria were constructed to achieve quantitative interpretation and evaluation of mud logging data. In the interpretation and evaluation of five wells in Zhage structure of Hetao Basin,the coincidence rate of interpretation while drilling is increased from 80.00% to 92.50%,which effectively reduces the human errors in the process of mud logging interpretation and evaluation,and provides a strong technical support for regional reservoir exploration and development.

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.

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.

Crude oil density is a very important physical property parameter in oil-gas exploration and geologic reserve evaluation. Aiming at the peoblem of few methods for predicting crude oil density in Lufeng Sag, FLAIR logging light, medium and heavy component data, corresponding reservoir tests or density data of PVT samples is used as the research objects.The prediction model of reservoir crude oil density in Lufeng Sag is established by using multiple linear regression method. The results show that the multiple linear regression oil density prediction model is established by the above method,both the significance and fit tests are satisfactory, and absolute value of error between the predicted average oil density and the measured oil density is less than 0.02 g/cm³, the accuracy of prediction effect is higher and the quantitative evaluation of crude oil density is realized, which has certain guiding significance for reservoir sampling optimization productivity prediction and geologic reserve evaluation.

The prediction of drilling operation cycles is of significant importance for determining the scale of drilling investments, scheduling operations, and achieving exploration and development targets. Currently,the characteristic parameters of the drilling operation cycle prediction models are relatively simple, and the relationship between well sections is not considered, so it is difficult to adjust the predictive results according to the actual operation situation. Addressing these issues, this study focuses on exploratory wells in the Beibu Gulf block, analyzing factors that influence drilling operation time. The characteristic parameters for the model were optimized, and a random forest regression model was utilized to predict drilling operation cycles. The goodness of fit of the prediction models for drilling operations from initial opening to drilling the fourth well section is 0.980,0.947,0.903 and 0.823 respectively, which can meet the practical application requirements. But as the number of drilling different well sections increases, the model performance tends to decline due to the complexity of formation conditions and the extension of operation time. The strategy of pre-drilling prediction and real-time parameter adjustment can be used to continuously supplement the training samples to improve the adaptability of the model to the specific operation characteristics in the study area. Drilling operation cycle prediction is of great significance in the planning and cost assessment of subsequent drilling schemes, and has a certain popularized valve.