Impact Damage Testing Study of Shanxi-Beijing Natural Gas Pipeline Based on Decision Tree Rotary Tiller Operation

The North China Plain and the agricultural region are crossed by the Shanxi-Beijing natural gas pipeline.Resi-dents in the area use rototillers for planting and harvesting;however,the depth of the rototillers into the ground is greater than the depth of the pipeline,posing a significant threat to the safe operation of the pipeline.Therefore,it is of great significance to study the dynamic response of rotary tillers impacting pipelines to ensure the safe opera-tion of pipelines.This article focuses on the Shanxi-Beijing natural gas pipeline,utilizingfinite element simulation software to establish afinite element model for the interaction among the machinery,pipeline,and soil,and ana-lyzing the dynamic response of the pipeline.At the same time,a decision tree model is introduced to classify the damage of pipelines under different working conditions,and the boundary value and importance of each influen-cing factor on pipeline damage are derived.Considering the actual conditions in the hemp yam planting area,targeted management measures have been proposed to ensure the operational safety of the Shanxi-Beijing natural gas pipeline in this region.

Selection of candidate wells for re-fracturing in tight gas sand reservoirs using fuzzy inference

An artificial-intelligence based decision-making protocol is developed for tight gas sands to identify re-fracturing wells and used in case studies. The methodology is based on fuzzy logic to deal with imprecision and subjectivity through mathematical representations of linguistic vagueness, and is a computing system based on the concepts of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. Five indexes are used to characterize hydraulic fracture quality, reservoir characteristics, operational parameters, initial conditions, and production related to the selection of re-fracturing well, and each index includes 3 related parameters. The value of each index/parameter is grouped into three categories that are low, medium, and high. For each category, a trapezoidal membership function all related rules are defined. The related parameters of an index are input into the rule-based fuzzy-inference system to output value of the index. Another fuzzy-inference system is built with the reservoir index, operational index, initial condition index and production index as input parameters and re-fracturing potential index as output parameter to screen out re-fracturing wells. This approach was successfully validated using published data.

An experimental and numerical study of chemically enhanced water alternating gas injection

In this work, an experimental study combined with numerical simulation was conducted to investigate the potential of chemically enhanced water alternating gas （CWAG） injection as a new enhanced oil recovery method. The unique feature of this new method is that it uses alkaline, surfactant, and polymer additives as a chemical slug which is injected during the water alternating gas （WAG） process to reduce the interfacial tension （IFT） and simultaneously improve the mobility ratio. In essence, the proposed CWAG process involves a combination of chemical flooding and immiscible carbon dioxide （CO2） injection and helps in IFT reduction, water blocking reduction, mobility control, oil swelling, and oil viscosity reduction due to CO2 dissolution. Its performance was compared with the conventional immiscible water alter- nating gas （I-WAG） flooding. Oil recovery utilizing CWAG was better by 26 % of the remaining oil in place after waterflooding compared to the recovery using WAG conducted under similar conditions. The coreflood data （cumulative oil and water production） were history mat- ched via a commercial simulator by adjusting the relative permeability curves and assigning the values of the rock and fluid properties such as porosity, permeability, and the experimentally determined IFT data. History matching ofthe coreflood model helped us optimize the experiments and was useful in determining the importance of the parameters influencing sweep efficiency in the CWAG process. The effectiveness of the CWAG process in pro- viding enhancement of displacement efficiency is evident in the oil recovery and pressure response observed in the coreflood. The results of sensitivity analysis on CWAG slug patterns show that the alkaline-surfactant-polymer injection is more beneficial after CO2 slug injection due to oil swelling and viscosity reduction. The CO2 slug size analysis shows that there is an optimum CO2 slug size, around 25 % pore volume which leads to a maximum oil recovery in the CWAG process. This study shows that the ultralow IFT system, i.e., IFT equaling 10 2 or 10 3 mN/ m, is a very important parameter in CWAG process since the water blocking effect can be minimized.

Effects of Different Concentrations of Sulfate Ions on Carbonate Crude Oil Desorption:Experimental Analysis and Molecular Simulation

Low salinity water containing sulfate ions can significantly alter the surface wettability of carbonate rocks.Nevertheless,the impact of sulfate concentration on the desorption of oil film on the surface of carbonate rock is still unknown.This study examines the variations in the wettability of the surface of carbonate rocks in solutions containing varying amounts of sodium sulfate and pure water.The problem is addressed in the framework of molecular dynamics simulation(Material Studio software)and experiments.The experiment’s findings demonstrate that sodium sulfate can increase the rate at which oil moisture is turned into water moisture.The final contact angle is smaller than that of pure water.The results of the simulations show that many water molecules travel down the water channel under the influence of several powerful forces,including the electrostatic force,the van der Waals force and hydrogen bond,crowding out the oil molecules on the calcite’s surface and causing the oil film to separate.The relative concentration curve of water and oil molecules indicates that the separation rate of the oil film on the surface of calcite increases with the number of sulfate ions.

Gas/water foams stabilized with a newly developed anionic surfactant for gas mobility control applications

Carbon dioxide(CO2) flooding is one of the most globally used EOR processes to enhance oil recovery.However,the low gas viscosity and density result in gas channeling and gravity override which lead to poor sweep efficiency.Foam application for mobility control is a promising technology to increase the gas viscosity,lower the mobility and improve the sweep efficiency in the reservoir.Foam is generated in the reservoir by co-injection of surfactant solutions and gas.Although there are many surfactants that can be used for such purpose,their performance with supercritical CO2(ScCO2) is weak causing poor or loss of mobility control.This experimental study evaluates a newly developed surfactant(CNF) that was introduced for ScCO2 mobility control in comparison with a common foaming agent,anionic alpha olefin sulfonate(AOS) surfactant.Experimental work was divided into three stages:foam static tests,interfacial tension measurements,and foam dynamic tests.Both surfactants were investigated at different conditions.In general,results show that both surfactants are good foaming agents to reduce the mobility of ScCO2 with better performance of CNF surfactant.Shaking tests in the presence of crude oil show that the foam life for CNF extends to more than 24 h but less than that for AOS.Moreover,CNF features lower critical micelle concentration(CMC),higher adsorption,and smaller area/molecule at the liquid-air interface.Furthermore,entering,spreading,and bridging coefficients indicate that CNF surfactant produces very stable foam with light crude oil in both deionized and saline water,whereas AOS was stable only in deionized water.At all conditions for mobility reduction evaluation,CNF exhibits stronger flow resistance,higher foam viscosity,and higher mobility reduction factor than that of AOS surfactant.In addition,CNF and ScCO2 simultaneous injection produced 8.83% higher oil recovery than that of the baseline experiment and 7.87% higher than that of AOS.Pressure drop profiles for foam flooding using CNF was slightly higher than that of AOS indicating that CNF is better in terms of foam-oil tolerance which resulted in higher oil recovery.

Chemical treatment for sand production control:A review of materials,methods,and field operations

Sand production from loosely consolidated reservoirs is one of the critical issues in the oil and gas in-dustry all around the world that can cause many problems,such as erosion of surface and well equip-ment,sand accumulation in wells and operation facilities,buckling of casing in cased-hole wells and well productivity reduction.Sand production control methods include restrictive production rate,mechanical methods(slotted liner,wire-wrapped screen,pre-packed screen,frac-pack,gravel pack,high-rate water pack)and chemical consolidation that chemical method is considered for more effectiveness in sand production alleviation due to increasing formation strength in near wellbore region.This review provides an overview on the laboratory and filed operation investigations of chemical remedy for sand production.Some used chemical agents and more common laboratory tests for evaluating the chemical performance in sand consolidation are introduced in this paper.Furthermore,the results of field operations and in-jections of chemicals into the desired formation are also reported.These results show that the chemical sand consolidation is more effective in newly perforated wells which have no sand production experi-ence and have a production history of less than two years.Finally,it was concluded that the main challenges in applying this method are permeability and capillary force reduction around the wellbore and selective injection into the targeted formation layers.

Relation between structural evolution of the Longmenshan orogenic zone and sedimentation of its foreland basin

In order to determine the area for oil and gas exploration in China’s north Sichuan basin,we have divided the time during which the Longmenshan foreland basin was formed into five periods,based on the sedimentary response relationship of the foreland basin to structural evolution: 1) a late Triassic Noric period;2) an early-Middle Jurassic period;3) a late Jurassic to early Cretaceous period;4) a late Cretaceous to Paleogene-Neogene period and 5) the Quaternary period. As well,we analyzed the sedimentary environment and lithologic features of every basin-forming period. The results show that there are several favorable source-reservoir-cap assemblages in our study area,making it a major region for future oil and gas exploration in China’s northern Sichuan basin.

Implementation of a Petrographical and Petrophysical Workflow Protocol for Studying the Impact of Heterogeneity on the Rock Typing and Reservoir Quality of Reefal Limestone:A Case Study on the Nullipore Carbonates in the Gulf of Suez

This study focuses on the heterogeneity of the middle Miocene syn-rift Belayim nullipore(reefal)marine sequences in the Gulf of Suez and its impacts on reservoir quality.The sequences consist of coralline algal reef limestones with a highly complex dual-porosity system of primary and secondary porosities of widely varying percentages.To achieve a precise mathematical modeling of these reservoir sequences,a workflow protocol was applied to separate these sequences into a number of hydraulic flow units(HFUs)and reservoir rock types(RRTs).This has been achieved by conducting a conventional core analysis on the nullipore marine sequence.To illustrate the heterogeneity of the nullipore reservoir,the Dykstra-Parsons coefficient(V)has been estimated(V=0.91),indicating an extremely heterogeneous reservoir.A slight to high anisotropy(λ_(k))has been assigned for the studied nullipore sequences.A stratigraphic modified Lorenz plot(SMLP)was applied to define the optimum number of HFUs and barriers/baffles in each of the studied wells.Integrating the permeability-porosity,reservoir quality index-normalized porosity index(RQI-NPI)and the RQI-flow zone indicator(RQIFZI)plots,the discrete rock types(DRT)and the R35 techniques enable the discrimination of the reservoir sequences into 4 RRTs/HFUs.The RRT4 packstone samples are characterized by the best reservoir properties(moderate permeability anisotropy,with a good-to-fair reservoir quality index),whereas the RRT1 mudstone samples have the lowest flow and storage capacities,as well as the tightest reservoir quality.

Investigation of the effect of diethylene triamine pentaacetic acid chelating agent as an enhanced oil recovery fluid on wettability alteration of sandstone rocks

This study used the diethylene triamine pentaacetic acid(DTPA)-seawater(SW)system to modify the sandstone rock wettability and enhance oil recovery.The investigation involved conducting wettability measurement,Zeta potential measurement,and spontaneous imbibition experiment.The introduction of 5%DTPA-sW solution resulted in a significant decrease in the rock-oil contact angle from 143°to 23,along with a reduction in the Zeta potential from-2.29 mV to-13.06 mV,thereby altering the rock surface charge and shifting its wettability from an oil-wet state to a strongly water-wet state.The presence or absence of potential determining ions(Ca^(2+),Mg^(2+),SO_(4)^(2-))in the solution did not impact the effectiveness of DTPA in changing the rock wettability.However,by tripling the concentration of these ions in the solution,the performance of 5%DTPA-SW solution in changing wettability was impaired.Additionally,spontaneous imbibition tests demonstrated that the 5%DTPA-SW solution led to an increase in oil recovery up to 39.6%.Thus,the optimum mass fraction of DTPA for changing sandstone wettability was determined to be5%.

Impact of clay stabilizer on the methane desorption kinetics and isotherms of Longmaxi Shale,China

Knowing methane desorption characteristics is essential to define the contribution of adsorbed gas to gas well production.To evaluate the synthetic effect of a clay stabilizer solution on methane desorption kinetics and isotherms pertaining to Longmaxi shale,an experimental setup was designed based on the volumetric method.The objective was to conduct experiments on methane adsorption and desorption kinetics and isotherms before and after clay stabilizer treatments.The experimental data were a good fit for both the intraparticle diffusion model and the Freundlich isotherm model.We analyzed the effect of the clay stabilizer on desorption kinetics and isotherms.Results show that clay stabilizer can obviously improve the diffusion rate constant and reduce the methane adsorption amount.Moreover,we analyzed the desorption efficiency before and after treatment as well as the adsorbed methane content.The results show that a higher desorption efficiency after treatment can be observed when the pressure is higher than 6.84 MPa.Meanwhile,the adsorbed methane content before and after treatment all increase when the pressure decreases,and clay stabilizer can obviously promote the adsorbed methane to free gas when the pressure is lower than 19 MPa.This can also be applied to the optimization formulation of slickwater and the design of gas well production.

Analysis of Wellbore Flow in Shale Gas Horizontal Wells

Theflow behavior of shale gas horizontal wells is relatively complex,and this should be regarded as the main reason for which conventional pipeflow models are not suitable to describe the related dynamics.In this study,numerical simulations have been conducted to determine the gas-liquid distribution in these wells.In particular,using the measuredflow pressure data related to 97 groups of shale gas wells as a basis,9 distinct pipeflow models have been assessed,and the models displaying a high calculation accuracy for different water-gas ratio(WGR)ranges have been identified.The results show that:(1)The variation law of WGR in gas well satisfies a power function relation.(2)The well structure is the main factor affecting the gas-liquid distribution in the wellbore.(3)The Beggs&Brill,Hagedorn&Brown and Gray models exhibit a high calculation accuracy.

Modeling, analysis, and screening of cyclic pressure pulsing with nitrogen in hydraulically fractured wells

Cyclic pressure pulsing with nitrogen is studied for hydraulically fractured wells in depleted reservoirs.A compositional simulation model is constructed to represent the hydraulic fractures through local-grid refinement.The process is analyzed from both operational and reservoir/hydraulic-fracture perspectives.Key sensitivity parameters for the operational component are chosen as the injection rate,lengths of injection and soaking periods and the economic rate limit to shut-in the well.For the reservoir/hydraulic fracturing components,reservoir permeability,hydraulic fracture permeability,effective thickness and half-length are used.These parameters are varied at five levels.A full-factorial experimental design is utilized to run 1250 cases.The study shows that within the ranges studied,the gas-injection process is applied successfully for a 20-year project period with net present values based on the incremental recoveries greater than zero.It is observed that the cycle rate limit,injection and soaking periods must be optimized to maximize the efficiency.The simulation results are used to develop a neural network based proxy model that can be used as a screening tool for the process.The proxy model is validated with blind-cases with a correlation coefficient of 0.96.

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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.

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

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.

Study on Optimal Water ControlMethods for Horizontal Wells in Bottom Water Clastic Rock Reservoirs

The segmented water control technology for bottom water reservoirs can effectively delay the entry of bottom water and adjust the production profile.To clarify the impact of different methods on horizontal well production with different reservoir conditions and to provide theoretical support for the scientific selection of methods for bottom water reservoirs,a numerical simulation method is presented in this study,which is able to deal with wellbore reservoir coupling under screen tube,perforation,and ICD(Inflow Control Device)completion.Assuming the geological characteristics of the bottom-water conglomerate reservoir in the Triassic Formation of the Tahe Block 9 as a test case,the three aforementioned completion methods are tested to predict the transient production characteristics.The impact of completion parameters,reservoir permeability,bottom-water energy,and individual well control on the time to encounter water in horizontal wells(during a water-free production period)is discussed.A boundary chart for the selection of completion methods is introduced accordingly.The results show that the optimized ICD completion development effect for heterogeneous reservoirs is the best,followed by optimized perforation completion.Permeability is the main factor affecting the performances of completion methods,while bottom water energy and single well controlled reserves have a scarce impact.The average permeability of the reservoir is less than 500 mD,and ICD has the best water control effect.If the permeability is greater than 500 mD,the water control effect of perforation completion becomes a better option.

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

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.

Applications of artificial intelligence in geothermal resource exploration: A review

Artificial intelligence (AI) has become increasingly important in geothermal exploration,significantly improving the efficiency of resource identification.This review examines current AI applications,focusing on the algorithms used,the challenges addressed,and the opportunities created.In addition,the review highlights the growth of machine learning applications in geothermal exploration over the past decade,demonstrating how AI has improved the analysis of subsurface data to identify potential resources.AI techniques such as neural networks,support vector machines,and decision trees are used to estimate subsurface temperatures,predict rock and fluid properties,and identify optimal drilling locations.In particular,neural networks are the most widely used technique,further contributing to improved exploration efficiency.However,the widespread adoption of AI in geothermal exploration is hindered by challenges,such as data accessibility,data quality,and the need for tailored data science training for industry professionals.Furthermore,the review emphasizes the importance of data engineering methodologies,data scaling,and standardization to enable the development of accurate and generalizable AI models for geothermal exploration.It is concluded that the integration of AI into geothermal exploration holds great promise for accelerating the development of geothermal energy resources.By effectively addressing key challenges and leveraging AI technologies,the geothermal industry can unlock cost‐effective and sustainable power generation opportunities.

Log interpretation of carbonate rocks based on petrophysical facies constraints

The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in the study area,combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs,a log interpretation technology route of“geological information constraint+deep learning”was developed.The principal component analysis(PCA)was employed to establish lithology identification criteria with an accuracy of 91%.The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%.Based on production data,the main lithologies and sedimentary microfacies of effective reservoirs were determined,and 10 petrophysical facies with effective reservoir characteristics were identified.Constrained by petrophysical facies,the mean interpretation error of porosity compared to core analysis results is 2.7%,and the ratio of interpreted permeability to core analysis is within one order of magnitude,averaging 3.6.The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data.Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs.

Road Layout Cuts Volume Evaluation by Electrical Resistivity Tomography: Case Study of Gagnoa-Gueyo-Bamenadou Road Project

A study of excavated material on the Gagnoa-Guéyo-Bamenadou road project in southwest Côte d’Ivoire was carried out using electrical resistivity tomography with a dipole-dipole configuration. This study aimed to determine the nature and volume of the studied cuts. Based on the cumulative distances of the longitudinal sections of the road alignment superimposed on the tomographic profiles, a cumulative volume of 104681 m3 of material was determined. This volume comprises 88557 m3 of soft cuts and 16,124 m3 of rocky cuts, which can be reused in specific embankment zones. This work may, therefore be useful in the characterization of cuts in a preliminary design study, in order to anticipate changes during the road’s development and asphalting.

含碳酸钙的海泡石钻井液的封堵性能

通过室内实验和理论分析,研究了不同温度、压力条件下添加碳酸钙前后海泡石水基钻井液对不同渗透性地层的封堵性能,论证将碳酸钙作为堵漏剂添加到海泡石钻井液中的可行性。在实验温度为27~204℃、实验压力为2 070 kPa和6 895 kPa条件下进行流变性和滤失性测试,结果表明,除了在149℃时,其他各温度下海泡石钻井液流变性质较好、悬固能力较强,高温高压滤失量较低。孔隙堵塞器(PPA)实验中用孔径10~90μm的渗透性陶瓷盘模拟地层,实验结果表明,不含碳酸钙的海泡石钻井液不能封堵孔隙,而含碳酸钙的海泡石钻井液可在较短时间内封堵孔隙,且在高温下也能保持碳酸钙颗粒悬浮,使用温度可高达193℃。扫描电镜分析及理想充填理论分析结果验证了PPA实验结果。