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Analysis of mechanical strengths of extreme line casing joint considering geometric, material, and contact nonlinearities

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petroleum Science 2024年第3期21卷 1992-2004页

作者： Ji-Yun Zhang Chi Peng Jian-Hong Fu Quan Cao Yu Su Jian-Yun Pang Zi-Qiang Yu petroleum engineering school Southwest Petroleum University engineering Technology Research Institute of CNPC Southwest Oil and gas Field Company

To address the challenges associated with difficult casing running, limited annular space, and poor cementing quality in the completion of ultra-deep wells, the extreme line casing offers an effective solution over conventional casings. However, due to its smaller size, the joint strength of extreme line casing is reduced, which may cause failure when running in the hole. To address this issue, this study focuses on the CST-ZT Φ139.7 mm × 7.72 mm extreme line casing and employs the elastic-plastic mechanics to establish a comprehensive analysis of the casing joint, taking into account the influence of geometric and material nonlinearities. A finite element model is developed to analyze the forces and deformations of the extreme line casing joint under axial tension and external collapse load. The model investigates the stress distribution of each thread tooth subjected to various tensile forces and external pressures. Additionally, the tensile strength and crushing strength of the extreme line casing joint are determined through both analytical and experimental approaches. The findings reveal that, under axial tensile load, the bearing surface of each thread tooth experiences uneven stress, with relatively high equivalent stress at the root of each thread tooth. The end thread teeth are valuable spots for failure. It is observed that the critical fracture axial load of thread decreases linearly with the increase of thread tooth sequence. Under external pressure, the circumferential stress is highest at the small end of the external thread, leading to yield deformation. The tensile strength of the joint obtained from the finite element model exhibits a relative error of less than 7% compared to the analytical and experimental values,proving the reliability of the finite element model. The tensile strength of the joint is 3091.9 k N.Moreover, in terms of anti-collapse capability, the joints demonstrate higher resistance to collapse compared to the casing body, which is consistent with the test results where the pip

关键词： Extreme line casing Elastic-plastic mechanics Finite element analysis Tensile strength Collapse strength

Experimental and numerical simulation study on the erosion behavior of the elbow of gathering pipeline in shale gas field

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petroleum Science 2024年第2期21卷 1257-1274页

作者： En-Bin Liu Shen Huang Ding-Chao Tian Lai-Min Shi Shan-Bi Peng He Zheng petroleum engineering school Southwest Petroleum UniversityChengdu 610500SichuanChina Chongqing natural gas Sales Center Natural Gas BranchSinopecChongqing400023China Zhejiang Zheneng natural gas Operation Co. Ltd.Hangzhou 310000ZhejiangChina school of Civil engineering and Architecture Southwest Petroleum UniversityChengdu 610500SichuanChina Louisiana Tech Univ Trenchless Technol Ctr599 Dan Reneau DrRustonLA71270USA Southwest Oil and gas Field Branch natural gas Research Institute Chengdu 610213SichuanChina

During the production period of shale gas, proppant particles and rock debris are produced together,which will seriously erode the elbows of gathering pipelines. In response to this problem, this paper takes the elbow of the gathering pipeline in the Changning Shale gas Field as an example to test the erosion rate and material removal mechanism of the test piece at different angles of the elbow through experiments and compares the four erosion models with the experimental results. Through analysis, it is found that the best prediction model for quartz sand-carbon steel erosion is the Oka model. Based on the Oka model, FLUENT software was used to simulate and analyze the law of erosion of the elbow of the gas gathering pipeline under different gas flow velocities, gas gathering pressure, particle size, length of L1,and bending directions of the elbow. And a spiral pipeline structure is proposed to reduce the erosion rate of the elbow under the same working conditions. The results show that this structure can reduce erosion by 34%.

关键词： Shale gas gas gathering pipeline Elbow Erosion CFD

A New Heat Transfer Model for Multi-Gradient Drilling with Hollow Sphere Injection

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Fluid Dynamics & Materials Processing 2024年第3期20卷 537-546页

作者： Jiangshuai Wang Chuchu Cai Pan Fu Jun Li Hongwei Yang Song Deng school of petroleum and natural gas engineering Changzhou UniversityChangzhouChina CNPC Research Institute of engineering Technology Co. Ltd.BeijingChina National engineering Research Center for Oil&gas Drilling and Completion Technology BeijingChina College of petroleum engineering China University of Petroleum(Beijing)BeijingChina College of petroleum Karamay CampusChina University of Petroleum(Beijing)BeijingChina

Multi-gradient drilling is a new offshore drilling method.The accurate calculation of the related wellbore temperature is of great significance for the prediction of the gas hydrate formation area and the precise control of the wellbore pressure.In this study,a new heat transfer model is proposed by which the variable mass flow is properly taken into account.Using this model,the effects of the main factors influencing the wellbore temperature are analyzed.The results indicate that at the position where the separation injection device is installed,the temperature increase of the fluid in the drill pipe is mitigated due to the inflow/outflow of hollow spheres,and the temperature drop of the fluid in the annulus also decreases.In addition,a lower separation efficiency of the device,a shallower installation depth and a smaller circulating displacement tend to increase the temperature near the bottom of the annulus,thereby helping to reduce the hydrate generation area and playing a positive role in the prevention and control of hydrates in deepwater drilling.

关键词： Multi-gradient drilling wellbore temperature hydrate separate injection device variable mass

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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petroleum Science 2024年第1期21卷 535-550页

作者： Song Deng Hao-Yu Pan Hai-Ge Wang Shou-Kun Xu Xiao-Peng Yan Chao-Wei Li Ming-Guo Peng Hao-Ping Peng Lin Shi Meng Cui Fei Zhao school of petroleum and natural gas engineering Changzhou UniversityChangzhou213164JiangsuChina Tubular Goods Research Institute of CNPC Beijing102249China CNPC engineering Technology R&D Company Limited Beijing102206China

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling efficiency.Traditional methods for predicting pore pressure are limited when forming particular structures and lithology.In this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure.This study collects data from three wells.Well 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model testing.In this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure modeling.In addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)algorithm.The IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training data.For the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and 0.9574.MLP achieves optimal performance on both training and test data,and the MLP model shows a high degree of generalization.It indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

关键词： Pore pressure Grey wolf optimization Multilayer perceptron Effective stress Machine learning

A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

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petroleum Science 2024年第2期21卷 1135-1148页

作者： Tie Yan Rui Xu Shi-Hui Sun Zhao-Kai Hou Jin-Yu Feng school of petroleum engineering Northeast Petroleum UniversityDaqing163318HeilongjiangChina Sanya Offshore Oil&gas Research Institute Northeast Petroleum UniversitySanya572025HainanChina

Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation.

关键词： Intelligent drilling Closed-loop drilling Lithology identification Random forest algorithm Feature extraction

Combined use of fly ash and silica to prevent the long-term strength retrogression of oil well cement set and cured at HPHT conditions

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petroleum Science 2024年第2期21卷 1122-1134页

作者： Guo-Dong Cheng Xue-Yu Pang Jin-Sheng Sun Zheng-Song Qiu Chuang-Chuang Wang Jian-Kun Qin Ning Li school of petroleum engineering China University of Petroleum(East China)Qingdao266580ShandongChina National Key Laboratory of Deep Oil and gas China University of Petroleum(East China)Qingdao266580ShandongChina Oil and gas engineering Research Institute(Tarim Oilfield Company) China National Petroleum CorporationTarim841000XinjiangChina

The long-term strength retrogression of silica-enriched oil well cement poses a significant threat to wellbore integrity in deep and ultra-deep wells, which is a major obstacle for deep petroleum and geothermal energy development. Previous attempts to address this problem has been unsatisfactory because they can only reduce the strength decline rate. This study presents a new solution to this problem by incorporating fly ash to the traditional silica-cement systems. The influences of fly ash and silica on the strength retrogression behavior of oil well cement systems directly set and cured under the condition of 200°C and 50 MPa are investigated. Test results indicate that the slurries containing only silica or fly ash experience severe strength retrogression from 2 to 30 d curing, while the slurries containing both fly ash and silica experience strength enhancement from 2 to 90 d. The strength test results are corroborated by further evidences from permeability tests as well as microstructure analysis of set cement. Composition of set cement evaluated by quantitative X-ray diffraction analyses with partial or no known crystal structure(PONKCS) method and thermogravimetry analyses revealed that the conversion of amorphous C-(A)-S-H to crystalline phases is the primary cause of long-term strength retrogression.The addition of fly ash can reduce the initial amount of C-(A)-S-H in the set cement, and its combined use with silica can prevent the crystallization of C-(A)-S-H, which is believed to be the working mechanism of this new admixture in improving long-term strength stability of oil well cement systems.

关键词： Fly ash Long-term strength retrogression High temperature Quantitative X-ray diffraction(QXRD) Partial or no known crystal structure(PONKCS)

Finite Element Method Simulation of Wellbore Stability under Different Operating and Geomechanical Conditions

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Fluid Dynamics & Materials Processing 2024年第1期20卷 205-218页

作者： Junyan Liu Ju Liu Yan Wang Shuang Liu Qiao Wang Yihe Du Oil&gas Project Research Institute PetroChina Tarim Oilfield CompanyKorla841000China petroleum engineering school Southwest Petroleum UniversityChengdu610500China

The variation of the principal stress of formations with the working and geo-mechanical conditions can trigger wellbore instabilities and adversely affect the well completion.A finite element model,based on the theory of poro-elasticity and the Mohr-Coulomb rock damage criterion,is used here to analyze such a risk.The changes in wellbore stability before and after reservoir acidification are simulated for different pressure differences.The results indicate that the risk of wellbore instability grows with an increase in the production-pressure difference regardless of whether acidification is completed or not;the same is true for the instability area.After acidizing,the changes in the main geomechanical parameters(i.e.,elastic modulus,Poisson’s ratio,and rock strength)cause the maximum wellbore instability coefficient to increase.

关键词： Wellbore stability finite element acidizing operation well completion

A theoretical study on gaseous pollutant flushing of natural ventilation driven by buoyancy forces in industrial buildings

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Building Simulation 2024年第4期17卷 575-589页

作者： Jiawei Zhuang Genyang Chen Rumeng Yang Kun Han Dongdong Tian Yongfa Diao Henggen Shen school of Urban Construction Changzhou UniversityChangzhou213164China school of petroleum and natural gas engineering School of EnergyChangzhou UniversityChangzhou213164China College of Environmental Science and engineering Donghua UniversityShanghai201620China school of Architecture and Urban Planning Nanjing UniversityNanjing210093China

The acceleration of industrialization worsening indoor environments of industrial buildings has drawn more attention in recent years.natural ventilation can improve indoor air quality(IAQ)and reduce carbon emissions.To evaluate gaseous pollutant levels in industrial buildings for the development of buoyancy-driven natural ventilation,two theoretical models of pollutant flushing(Model I and Model II)are developed based on the existing thermal stratification theory in combination with the mixing characteristics of lower pollutant.The results show that indoor pollutant flushing is mainly dependent on the pollution source intensity and effective ventilation area.The mixing characteristics of lower pollutant has an important effect on pollutant stratification and evolution during ventilation,but it does not change the prediction results at steady state.When the dimensionless pollution source intensity is larger than 1,the pollution source should be cleaned up or other ventilation methods should be used instead to improve IAQ.In addition,the comparisons between Model I and Model II on instantaneous pollutant concentration are significantly influenced by the pollution source intensity,and the actual pollutant concentration is more likely to be between the predicted values of Model I and Model II.To reduce pollutant concentration to a required level,the pollution source intensity should be in a certain range.The theoretical models as well as the necessary conditions for ventilation effectiveness obtained can be used for the ventilation optimization design of industrial buildings.

关键词： industrial buildings buoyancy-driven natural ventilation gaseous pollutants evolution model pollution sources

Dynamic risk assessment of gas pipeline operation process by fusing visual and olfactory monitoring

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Journal of Safety Science and Resilience 2024年第2期5卷 156-166页

作者： Denglong Ma Weigao Mao Guangsen Zhang Chaoyi Liu Yi Han Xiaoming Zhang Hansheng Wang Kang Cen Wan Lu Denghui Li Hanyue Zhang school of Mechanical engineering Xi'an Jiaotong UniversityXi'an 710049China Hanzhong natural gas Investinent Development Co.Ltd Hanzhong723011China Shaanxi Special Equipment Inspection and Testing Institute Xi'an710038China school of Civil engineering and Architecture Southwest Petroleum UniversityChengdu610500China Sichuan Tianxin gas Co.Ltd. Mianyang62100China Petro China Southwest Oil and gas Field Company gas Branch Chengdu610500China

With the rapid increase in urban gas consumption,the frequency of maintenance and repair of gas pipelines has escalated,leading to a rise in safety accidents during these processes.The traditional manual supervision model presents challenges such as inaccurate monitoring results,incomplete risk factor analysis,and a lack of quantitative risk assessment.This research focuses on developing a dynamic risk assessment technology for gas emergency repair operations by integrating the monitoring outcomes of artificial olfactory for gas leakage information and video object recognition for visual safety factor monitoring data.To quantitatively evaluate the risk of the operation process,a three-dimensional risk assessment model combining gas leakage with riskcorrelated sensitivity was established as well as a separate three-dimensional risk assessment model integrating visual risk factors with predictable risk disposition.Furthermore,a visual risk quantification expression mode based on the risk matrix-radar map method was introduced.Additionally,a risk quantification model based on the fusion of visual and olfactory results was formulated.The verification results of simulation scenarios based on field data indicate that the visual-olfactory fusion risk assessment method can more accurately reflect the dynamic risk level of the operation process compared to simple visual safety factor monitoring.The outcomes of this research can contribute to the identification of safety status and early warning of risks related to personnel,equipment,and environmental factors in emergency repair operations.Moreover,these results can be extended to other operational scenarios,such as oil and gas production stations and long-distance pipeline operations.

关键词： gas pipelinemaintenance Dynamicriskassessment Visual-olfactoryfusion Risk matrix Risk quantification model