Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the g...Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.展开更多
Predicting the transition-temperature shift(TTS)induced by neutron irradiation in reactor pressure-vessel(RPV)steels is important for the evaluation and extension of nuclear power-plant lifetimes.Current prediction mo...Predicting the transition-temperature shift(TTS)induced by neutron irradiation in reactor pressure-vessel(RPV)steels is important for the evaluation and extension of nuclear power-plant lifetimes.Current prediction models may fail to properly describe the embrittlement trend curves of Chinese domestic RPV steels with relatively low Cu content.Based on the screened surveillance data of Chinese domestic and similar international RPV steels,we have developed a new fluencedependent model for predicting the irradiation-embrittlement trend.The fast neutron fluence(E>1 MeV)exhibited the highest correlation coefficient with the measured TTS data;thus,it is a crucial parameter in the prediction model.The chemical composition has little relevance to the TTS residual calculated by the fluence-dependent model.The results show that the newly developed model with a simple power-law functional form of the neutron fluence is suitable for predicting the irradiation-embrittlement trend of Chinese domestic RPVs,regardless of the effect of the chemical composition.展开更多
Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline rupture.Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety man...Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline rupture.Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management.Aiming at the shortcomings of the BP Neural Network(BPNN)model,such as low learning efficiency,sensitivity to initial weights,and easy falling into a local optimal state,an Improved Sparrow Search Algorithm(ISSA)is adopted to optimize the initial weights and thresholds of BPNN,and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established.Taking 61 sets of pipelines blasting test data as an example,the prediction model was built and predicted by MATLAB software,and compared with the BPNN model,GA-BPNN model,and SSA-BPNN model.The results show that the MAPE of the ISSA-BPNN model is 3.4177%,and the R2 is 0.9880,both of which are superior to its comparison model.Using the ISSA-BPNN model has high prediction accuracy and stability,and can provide support for pipeline inspection and maintenance.展开更多
Decreasing the risks and geohazards associated with drilling engineering in high-temperature high-pressure(HTHP) geologic settings begins with the implementation of pre-drilling prediction techniques(PPTs). To improve...Decreasing the risks and geohazards associated with drilling engineering in high-temperature high-pressure(HTHP) geologic settings begins with the implementation of pre-drilling prediction techniques(PPTs). To improve the accuracy of geopressure prediction in HTHP hydrocarbon reservoirs offshore Hainan Island, we made a comprehensive summary of current PPTs to identify existing problems and challenges by analyzing the global distribution of HTHP hydrocarbon reservoirs, the research status of PPTs, and the geologic setting and its HTHP formation mechanism. Our research results indicate that the HTHP formation mechanism in the study area is caused by multiple factors, including rapid loading, diapir intrusions, hydrocarbon generation, and the thermal expansion of pore fluids. Due to this multi-factor interaction, a cloud of HTHP hydrocarbon reservoirs has developed in the Ying-Qiong Basin, but only traditional PPTs have been implemented, based on the assumption of conditions that do not conform to the actual geologic environment, e.g., Bellotti's law and Eaton's law. In this paper, we focus on these issues, identify some challenges and solutions, and call for further PPT research to address the drawbacks of previous works and meet the challenges associated with the deepwater technology gap. In this way, we hope to contribute to the improved accuracy of geopressure prediction prior to drilling and provide support for future HTHP drilling offshore Hainan Island.展开更多
The structure of the pressure swirl nozzle is an important factor affecting its spray performance.This work aims to study pressure swirl nozzles with different structures by experiment and simulation.In the experiment...The structure of the pressure swirl nozzle is an important factor affecting its spray performance.This work aims to study pressure swirl nozzles with different structures by experiment and simulation.In the experiment,10 nozzles with different structures are designed to comprehensively cover various geometric factors.In terms of simulation,steady-state simulation with less computational complexity is used to study the flow inside the nozzle.The results show that the diameter of the inlet and outlet,the direction of the inlet,the diameter of the swirl chamber,and the height of the swirl chamber all affect the atomization performance,and the diameter of the inlet and outlet has a greater impact.It is found that under the same flow rate and pressure,the geometric differences do have a significant impact on the atomization characteristics,such as spray angle and SMD(Sauter mean diameter).Specific nozzle structures can be customized according to the actual needs.Data analysis shows that the spray angle is related to the swirl number,and the SMD is related to turbulent kinetic energy.Through data fitting,the equations for predicting the spray angle and the SMD are obtained.The error range of the fitting equation for the prediction of spray angle and SMD is within 15% and 10% respectively.The prediction is expected to be used in engineering to estimate the spray performance at the beginning of a real project.展开更多
This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Da...This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.展开更多
Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene(EPS)geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading.In this paper,t...Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene(EPS)geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading.In this paper,the failure mode and the earth pressure acting on the rigid retaining wall with EPS geofoam inclusions and granular backfills(henceforth referred to as EPS-wall),under limited surcharge loading are investigated through two-and three-dimensional model tests.The testing results show that different from the sliding of almost all the backfill in the EPS-wall under semi-infinite surcharge loading,only an approximately triangular backfill slides in the wall under limited surcharge loading.The distribution of the lateral earth pressure on the EPS-wall under limited surcharge loading is non-linear,and the distribution changes from the increase of the wall depth to the decrease with the increase of the limited surcharge loading.An approach based on the force equilibrium of a differential element is developed to predict the lateral earth pressure behind the EPS-wall subjected to limited surcharge loading,and its performance was fully validated by the three-dimensional model tests.展开更多
In this editorial,we comment on the minireview by Martino A,published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023;15(12):681-689.We focused mainly on the possibility of replacing the hepati...In this editorial,we comment on the minireview by Martino A,published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023;15(12):681-689.We focused mainly on the possibility of replacing the hepatic venous pressure gradient(HVPG)and endoscopy with noninvasive methods for predicting esophageal variceal bleeding.The risk factors for bleeding were the size of the varices,the red sign and the Child-Pugh score.The intrinsic core factor that drove these changes was the HVPG.Therefore,the present studies investigating noninvasive methods,including computed tomography,magnetic resonance imaging,elastography,and laboratory tests,are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes,such as bleeding.A single parameter is usually not enough to construct an efficient model.Therefore,multiple factors were used in most of the studies to construct predictive models.Encouraging results have been obtained,in which bleeding prediction was partly reached.However,these methods are not satisfactory enough to replace invasive methods,due to the many drawbacks of different studies.There is still plenty of room for future improvement.Prediction of the precise timing of bleeding using various models,and extracting the texture of variceal walls using high-definition imaging modalities to predict the red sign are interesting directions to lay investment on.展开更多
Helium,with a full-shell electronic structure,is the most inert element in the periodic table at atmospheric pressure.The study of the reaction between helium and other non-noble-gas elements as well as relevant compo...Helium,with a full-shell electronic structure,is the most inert element in the periodic table at atmospheric pressure.The study of the reaction between helium and other non-noble-gas elements as well as relevant compounds has attracted great attention in the fields of chemistry,physics,materials and planetary science.In this study,we found a stable compound of MgHe with P63/mmc symmetry at pressures above 795 GPa within zero-point energy.Thermodynamic stability calculations of P63/mmc phase at high temperatures and pressures indicate that this structure may exist in the interior of the super-Earth and Neptune.Our further simulations on the electron localization function and Bader analysis show that the predicted compound is an electride with-1.093e in the quantized interstitial quasiatom(ISQ)orbitals,which are localized at interstitial sites in the crystal lattice.Our study provides a theoretical basis for studying the physical and chemical properties of MgHe and the existence of MgHe in gaseous planets.展开更多
There are plentiful potential hydrocarbon resources in the Yinggehai and Qiongdongnan basins in the northern South China Sea. However, the special petrol-geological condition with high formation temperature and pressu...There are plentiful potential hydrocarbon resources in the Yinggehai and Qiongdongnan basins in the northern South China Sea. However, the special petrol-geological condition with high formation temperature and pressure greatly blocked hydrocarbon exploration. The conventional means of drills, including methods in the prediction and monitoring of underground strata pressure, can no longer meet the requirements in this area. The China National Offshore Oil Corporation has allocated one well with a designed depth of 3200 m and pressure coefficient of 2.3 in the Yinggehai Basin (called test well in the paper) in order to find gas reservoirs in middle-deep section in the Miocene Huangliu and Meishan formations at the depth below 3000 m. Therefore, combined with the '863' national high-tech project, the authors analyzed the distribution of overpressure in the Yinggehai and Qiongdongnan basins, and set up a series of key technologies and methods to predict and monitor formation pressure, and then apply the results to pressure prediction of the test well. Because of the exact pressure prediction before and during drilling, associated procedure design of casing and their allocation in test well has been ensured to be more rational. This well is successfully drilled to the depth of 3485 m (nearly 300 m deeper than the designed depth) under the formation pressure about 2.3 SG (EMW), which indicate that a new step in the technology of drilling in higher temperature and pressure has been reached in the China National Offshore Oil Corporation.展开更多
The main methods of coalbed methane(CBM)development are drainage and depressurization,and a precise prediction of coal reservoir pressure is thus crucial for the evaluation of reservoir potentials and the formulation ...The main methods of coalbed methane(CBM)development are drainage and depressurization,and a precise prediction of coal reservoir pressure is thus crucial for the evaluation of reservoir potentials and the formulation of reasonable development plans.This work established a new reservoir pressure prediction model based on the material balance equation(MBE)of coal reservoir,which considers the self-regulating effects of coal reservoirs and the dynamic change of equivalent drainage area(EDA).According to the proposed model,the reservoir pressure can be predicted based on reservoir condition data and the actual production data of a single well.Compared with traditional reservoir pressure prediction models which regard EDA as a fixed value,the proposed model can better predict the average pressure of reservoirs.Moreover,orthogonal experiments were designed to evaluate the sensitivity of reservoir parameters on the reservoir pressure prediction results of this proposed model.The results show that the saturation of irreducible water is the most sensitive parameter,followed by Langmuir volume and reservoir porosity,and Langmuir pressure is the least sensitive parameter.In addition,the pressure drop of reservoirs is negatively correlated with the saturation of irreducible water and the Langmuir volume,while it is positively correlated with porosity.This work analyzed the reservoir pressure drop characteristics of the CBM wells in the Shizhuangnan Block of the Qinshui Basin,and the results show that the CBM reservoir depressurization can be divided into three types,i.e.,rapidly drop type,medium-term stability type,and slowly drop type.The drainage features of wells were reasonably interpreted based on the comprehensive analysis of the reservoir depressurization type;the latter was coupled to the corresponding permeability dynamic change characteristics,eventually proving the applicability of the proposed model.展开更多
Overpressure in deepwater basins not only causes serious soft sediment deformation, but also significantly affects the safety of drilling operations. Therefore, prediction of overpressure in sediments has become an im...Overpressure in deepwater basins not only causes serious soft sediment deformation, but also significantly affects the safety of drilling operations. Therefore, prediction of overpressure in sediments has become an important task in deepwater oil exploration and development. In this study, we analyze the drilling data from ODP Leg 184 Sites 1144, 1146, and 1148, and IODP Leg 349 Sites U1431, U1432, U1433, and U1435 to study the sediment compaction and controls in the northern South China Sea. Sedimentation rate, sediment content, distribution area, and buried depth are the factors that influence sediment compaction in the deepwater basin of the South China Sea. Among these factors, the sediment content is the most important. The fitted normal compacted coefficients and mudline porosity for an interval of 50 m shows disciplinary variation versus depth. The pore pressure predicted from different fitted results shows varying overpressure situations. The normal compaction trend from Site 1144 reflects the porosity variation trend in stable deposition basins in the northern South China Sea. The predicted pore pressure shows overpressure at Site 1144, which is attributed to compaction disequilibrium. Nevertheless, the mixed lithology column may influence the predicted overpressure at Site 1148, which is responsible for the confusing result. Above all, we find that sediment compaction should serve as a proxy for pore pressure in the deepwater basin of the South China Sea.展开更多
The basis of designing gasified drilling is to understand the behavior of gas/liquid two-phase flow in the wellbore. The equations of mass and momentum conservation and equation of fluid flow in porous media were used...The basis of designing gasified drilling is to understand the behavior of gas/liquid two-phase flow in the wellbore. The equations of mass and momentum conservation and equation of fluid flow in porous media were used to establish a dynamic model to predict wellbore pressure according to the study results of Ansari and Beggs-Brill on gas-liquid two-phase flow. The dynamic model was solved by the finite difference approach combined with the mechanistic steady state model. The mechanistic dynamic model was numerically implemented into a FORTRAN 90 computer program and could simulate the coupled flow of fluid in wellbore and reservoir. The dynamic model revealed the effects of wellhead back pressure and injection rate of gas/liquid on bottomhole pressure. The model was validated against full-scale experimental data, and its 5.0% of average relative error could satisfy the accuracy requirements in engineering design.展开更多
Pore pressure is an essential parameter for establishing reservoir conditions,geological interpretation and drilling programs.Pore pressure prediction depends on information from various geophysical logs,seismic,and d...Pore pressure is an essential parameter for establishing reservoir conditions,geological interpretation and drilling programs.Pore pressure prediction depends on information from various geophysical logs,seismic,and direct down-hole pressure measurements.However,a level of uncertainty accompanies the prediction of pore pressure because insufficient information is usually recorded in many wells.Applying machine learning(ML)algorithms can decrease the level of uncertainty of pore pressure prediction uncertainty in cases where available information is limited.In this research,several ML techniques are applied to predict pore pressure through the over-pressured Eocene reservoir section penetrated by four wells in the Mangahewa gas field,New Zealand.Their predictions substantially outperform,in terms of prediction performance,those generated using a multiple linear regression(MLR)model.The geophysical logs used as input variables are sonic,temperature and density logs,and some direct pore pressure measurements were available at the reservoir level to calibrate the predictions.A total of 25,935 data records involving six well-log input variables were evaluated across the four wells.All ML methods achieved credible levels of pore pressure prediction performance.The most accurate models for predicting pore pressure in individual wells on a supervised basis are decision tree(DT),adaboost(ADA),random forest(RF)and transparent open box(TOB).The DT achieved root mean square error(RMSE)ranging from 0.25 psi to 14.71 psi for the four wells.The trained models were less accurate when deployed on a semi-supervised basis to predict pore pressure in the other wellbores.For two wells(Mangahewa-03 and Mangahewa-06),semi-supervised prediction achieved acceptable prediction performance of RMSE of 130—140 psi;while for the other wells,semi-supervised prediction performance was reduced to RMSE>300 psi.The results suggest that these models can be used to predict pore pressure in nearby locations,i.e.similar geology at corresponding depths within a field,but they become less reliable as the step-out distance increases and geological conditions change significantly.In comparison to other approaches to predict pore pressures,this study has identified that application of several ML algorithms involving a large number of data records can lead to more accurate prediction results.展开更多
This article proposes a water inrush mechanism of progressive intrusion of pressure water up into the coal floor aquiclude according to injection tests and observations. A numerical model and a criterion of water inru...This article proposes a water inrush mechanism of progressive intrusion of pressure water up into the coal floor aquiclude according to injection tests and observations. A numerical model and a criterion of water inrush are established based on the mechanism. The theory is succesSfully used in predictions of water inrush.展开更多
Yinggehai Basin locates in the northern South China Sea. Since the Cainozoic Era, crust has several strong tension: the basin subsides quickly, the deposition is thick, and the crust is thin. In the central basin, for...Yinggehai Basin locates in the northern South China Sea. Since the Cainozoic Era, crust has several strong tension: the basin subsides quickly, the deposition is thick, and the crust is thin. In the central basin, formation pressure coefficient is up to 2.1;Yinggehai Basin is a fomous high-temperature overpressure basin.YinggehaiBasin’s in-depth, especially high-temperature overpressure stratum has numerous large-scale exploration goals. As a result of high-temperature overpressure basin’s perplexing geological conditions and geophysical analysis technical limitations, this field of gas exploration can’t be carried out effectively, which affects the process of gas exploration seriously. A pressure prediction model of the high-temperature overpressure basin in different structural positions is summed up by pressure forecast pattern research in recent years, which can be applied to target wells pre-drilling pressure prediction and post drilling pressure analysis of Yinggehai Basin. The model has small erroneous and high rate of accuracy. The Yinggehai Basin A well drilling is successful in 2010, and gas is discovered in high-temperature overpressure stratum, which proved that reservoir can be found in high-temperature overpressure stratum. It is a great theoretical breakthrough of reservoir knowledge.展开更多
The accurate prediction of formation pressure is important in oil/gas exploration and development.However,the achievement of this goal remains challenging,due to insufficient logging data and the low predictive data a...The accurate prediction of formation pressure is important in oil/gas exploration and development.However,the achievement of this goal remains challenging,due to insufficient logging data and the low predictive data accuracy from seismic data.In this work,a case study was carried out in the Baima area of Wulong,in order to develop a workflow for accurately predicting shale gas formation pressure.The multi-channel stack method was first used,as well as the inversion of single-channel seismic data,to construct velocity and density models of the formation.Combined with the existing welllogging data,the velocity and density models of the whole well section were established.The shale gas formation pressure was then estimated using the Eaton method.The results show that the multi-channel seismic stacking method has a higher accuracy than the inversion of the formation velocity obtained by the single-channel seismic method.The discrepancies between our predicted formation pressure and the actual formation pressure measurement are within an acceptable range,indicating that our workflow is effective.展开更多
The accurate prediction of overpressure is one of the key issues that restrict the effective development of oil and gas resources in the Yinggehai Basin. In this paper, the formation mechanism of overpressure in Yingg...The accurate prediction of overpressure is one of the key issues that restrict the effective development of oil and gas resources in the Yinggehai Basin. In this paper, the formation mechanism of overpressure in Yinggehai Basin is studied. Based on this mechanism, the quantitative prediction model and empirical parameters of overpressure are optimized in Yinggehai Basin and applied in engineering. The results show that the formation mechanism of overpressure in the Yinggehai Basin is complicated, and the causes of overpressure in different blocks of basin are different. The eastern block mainly develops loading-type overpressure, while the Ledong block is dominated by unloading high pressure. Different blocks should employ different abnormal high-pressure prediction models. The East block mainly adopts the Eaton method, and the Ledong block mainly utilizes the Bowers method. The empirical parameters of different models can be determined according to the actual drilling conditions. The practical application demonstrates that the abnormal high-pressure prediction error is within 2%, and it is able to satisfy the requirements of on-site engineering.展开更多
The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion,...The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion, the calculations were carried out for non-isotherm VPB at various temperatures and the influences of the initial temperature of viscous medium on failure mode of bulge specimens were investigated. The results show that the failure modes are different for the non-isothermal VPB with different initial temperatures of viscous medium. For the non-isothermal VPB of AA3003 aluminum alloy sheet with initial temperature of 250 ℃, when the initial temperature of viscous medium ranges from 150 to 180 ℃, the formability of sheet metal can be improved to a full extent. The validity of the predictions is examined by comparing with experimental results.展开更多
基金funded by the National Natural Science Foundation of China(General Program:No.52074314,No.U19B6003-05)National Key Research and Development Program of China(2019YFA0708303-05)。
文摘Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.
基金supported by the National Key R&D Program of China (No. 2019YFB1900901)the Fundamental Research Funds for the Central Universities (No. 2021MS032)
文摘Predicting the transition-temperature shift(TTS)induced by neutron irradiation in reactor pressure-vessel(RPV)steels is important for the evaluation and extension of nuclear power-plant lifetimes.Current prediction models may fail to properly describe the embrittlement trend curves of Chinese domestic RPV steels with relatively low Cu content.Based on the screened surveillance data of Chinese domestic and similar international RPV steels,we have developed a new fluencedependent model for predicting the irradiation-embrittlement trend.The fast neutron fluence(E>1 MeV)exhibited the highest correlation coefficient with the measured TTS data;thus,it is a crucial parameter in the prediction model.The chemical composition has little relevance to the TTS residual calculated by the fluence-dependent model.The results show that the newly developed model with a simple power-law functional form of the neutron fluence is suitable for predicting the irradiation-embrittlement trend of Chinese domestic RPVs,regardless of the effect of the chemical composition.
文摘Oil and gas pipelines are affected by many factors,such as pipe wall thinning and pipeline rupture.Accurate prediction of failure pressure of oil and gas pipelines can provide technical support for pipeline safety management.Aiming at the shortcomings of the BP Neural Network(BPNN)model,such as low learning efficiency,sensitivity to initial weights,and easy falling into a local optimal state,an Improved Sparrow Search Algorithm(ISSA)is adopted to optimize the initial weights and thresholds of BPNN,and an ISSA-BPNN failure pressure prediction model for corroded pipelines is established.Taking 61 sets of pipelines blasting test data as an example,the prediction model was built and predicted by MATLAB software,and compared with the BPNN model,GA-BPNN model,and SSA-BPNN model.The results show that the MAPE of the ISSA-BPNN model is 3.4177%,and the R2 is 0.9880,both of which are superior to its comparison model.Using the ISSA-BPNN model has high prediction accuracy and stability,and can provide support for pipeline inspection and maintenance.
基金funded by the National Basic Research Program of China (No. 2015CB251201)the NSFC-Shandong Joint Fund for Marine Science Research Centers (No. U1606401)+3 种基金the Scientific and Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology (No. 2016ASKJ13)the Major National Science and Technology Programs (No. 016ZX05024-001-002)the Natural Science Foundation of Hainan (No. ZDYF2016215)Key Science and Technology Foundation of Sanya (Nos. 2017PT13, 2017PT2014)
文摘Decreasing the risks and geohazards associated with drilling engineering in high-temperature high-pressure(HTHP) geologic settings begins with the implementation of pre-drilling prediction techniques(PPTs). To improve the accuracy of geopressure prediction in HTHP hydrocarbon reservoirs offshore Hainan Island, we made a comprehensive summary of current PPTs to identify existing problems and challenges by analyzing the global distribution of HTHP hydrocarbon reservoirs, the research status of PPTs, and the geologic setting and its HTHP formation mechanism. Our research results indicate that the HTHP formation mechanism in the study area is caused by multiple factors, including rapid loading, diapir intrusions, hydrocarbon generation, and the thermal expansion of pore fluids. Due to this multi-factor interaction, a cloud of HTHP hydrocarbon reservoirs has developed in the Ying-Qiong Basin, but only traditional PPTs have been implemented, based on the assumption of conditions that do not conform to the actual geologic environment, e.g., Bellotti's law and Eaton's law. In this paper, we focus on these issues, identify some challenges and solutions, and call for further PPT research to address the drawbacks of previous works and meet the challenges associated with the deepwater technology gap. In this way, we hope to contribute to the improved accuracy of geopressure prediction prior to drilling and provide support for future HTHP drilling offshore Hainan Island.
基金supported by the National Key Research and Development Program(2022YFB3504000)the National Natural Science Foundation of China(22122815,21978296)the NSFC-EU project(31961133018)。
文摘The structure of the pressure swirl nozzle is an important factor affecting its spray performance.This work aims to study pressure swirl nozzles with different structures by experiment and simulation.In the experiment,10 nozzles with different structures are designed to comprehensively cover various geometric factors.In terms of simulation,steady-state simulation with less computational complexity is used to study the flow inside the nozzle.The results show that the diameter of the inlet and outlet,the direction of the inlet,the diameter of the swirl chamber,and the height of the swirl chamber all affect the atomization performance,and the diameter of the inlet and outlet has a greater impact.It is found that under the same flow rate and pressure,the geometric differences do have a significant impact on the atomization characteristics,such as spray angle and SMD(Sauter mean diameter).Specific nozzle structures can be customized according to the actual needs.Data analysis shows that the spray angle is related to the swirl number,and the SMD is related to turbulent kinetic energy.Through data fitting,the equations for predicting the spray angle and the SMD are obtained.The error range of the fitting equation for the prediction of spray angle and SMD is within 15% and 10% respectively.The prediction is expected to be used in engineering to estimate the spray performance at the beginning of a real project.
基金support by the National Natural Science Foundation of China(Grant Nos.52108377,52090084,and 51938008).
文摘This research explores the potential for the evaluation and prediction of earth pressure balance shield performance based on a gray system model.The research focuses on a shield tunnel excavated for Metro Line 2 in Dalian,China.Due to the large error between the initial geological exploration data and real strata,the project construction is extremely difficult.In view of the current situation regarding the project,a quantitative method for evaluating the tunneling efficiency was proposed using cutterhead rotation(R),advance speed(S),total thrust(F)and torque(T).A total of 80 datasets with three input parameters and one output variable(F or T)were collected from this project,and a prediction framework based gray system model was established.Based on the prediction model,five prediction schemes were set up.Through error analysis,the optimal prediction scheme was obtained from the five schemes.The parametric investigation performed indicates that the relationships between F and the three input variables in the gray system model harmonize with the theoretical explanation.The case shows that the shield tunneling performance and efficiency are improved by the tunneling parameter prediction model based on the gray system model.
基金funding support from National Natural Science Foundation of China(Grant No.52179109)Jiangsu Provincial Natural Science Foundation(Grant No.BK20230967)Open Research Fund of State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures,Shijiazhuang Tiedao University(Grant No.KF2022-02).
文摘Existing studies have focused on the behavior of the retaining wall equipped with expanded polystyrene(EPS)geofoam inclusions under semi-infinite surcharge loading rather than limited surcharge loading.In this paper,the failure mode and the earth pressure acting on the rigid retaining wall with EPS geofoam inclusions and granular backfills(henceforth referred to as EPS-wall),under limited surcharge loading are investigated through two-and three-dimensional model tests.The testing results show that different from the sliding of almost all the backfill in the EPS-wall under semi-infinite surcharge loading,only an approximately triangular backfill slides in the wall under limited surcharge loading.The distribution of the lateral earth pressure on the EPS-wall under limited surcharge loading is non-linear,and the distribution changes from the increase of the wall depth to the decrease with the increase of the limited surcharge loading.An approach based on the force equilibrium of a differential element is developed to predict the lateral earth pressure behind the EPS-wall subjected to limited surcharge loading,and its performance was fully validated by the three-dimensional model tests.
文摘In this editorial,we comment on the minireview by Martino A,published in the recent issue of World Journal of Gastrointestinal Endoscopy 2023;15(12):681-689.We focused mainly on the possibility of replacing the hepatic venous pressure gradient(HVPG)and endoscopy with noninvasive methods for predicting esophageal variceal bleeding.The risk factors for bleeding were the size of the varices,the red sign and the Child-Pugh score.The intrinsic core factor that drove these changes was the HVPG.Therefore,the present studies investigating noninvasive methods,including computed tomography,magnetic resonance imaging,elastography,and laboratory tests,are working on correlating imaging or serum marker data with intravenous pressure and clinical outcomes,such as bleeding.A single parameter is usually not enough to construct an efficient model.Therefore,multiple factors were used in most of the studies to construct predictive models.Encouraging results have been obtained,in which bleeding prediction was partly reached.However,these methods are not satisfactory enough to replace invasive methods,due to the many drawbacks of different studies.There is still plenty of room for future improvement.Prediction of the precise timing of bleeding using various models,and extracting the texture of variceal walls using high-definition imaging modalities to predict the red sign are interesting directions to lay investment on.
基金Project supported by the Natural Science Foundation of Shandong Province(Grant No.ZR202103010004)the China Postdoctoral Science Foundation(Certificate Nos.2023T160396 and 2021M691980)+1 种基金the National Natural Science Foundation of China(Grant Nos.12204280 and 12147135)the Youth Innovation Team Plan of Colleges and Universities in Shandong Province(Grant No.2023KJ350).
文摘Helium,with a full-shell electronic structure,is the most inert element in the periodic table at atmospheric pressure.The study of the reaction between helium and other non-noble-gas elements as well as relevant compounds has attracted great attention in the fields of chemistry,physics,materials and planetary science.In this study,we found a stable compound of MgHe with P63/mmc symmetry at pressures above 795 GPa within zero-point energy.Thermodynamic stability calculations of P63/mmc phase at high temperatures and pressures indicate that this structure may exist in the interior of the super-Earth and Neptune.Our further simulations on the electron localization function and Bader analysis show that the predicted compound is an electride with-1.093e in the quantized interstitial quasiatom(ISQ)orbitals,which are localized at interstitial sites in the crystal lattice.Our study provides a theoretical basis for studying the physical and chemical properties of MgHe and the existence of MgHe in gaseous planets.
文摘There are plentiful potential hydrocarbon resources in the Yinggehai and Qiongdongnan basins in the northern South China Sea. However, the special petrol-geological condition with high formation temperature and pressure greatly blocked hydrocarbon exploration. The conventional means of drills, including methods in the prediction and monitoring of underground strata pressure, can no longer meet the requirements in this area. The China National Offshore Oil Corporation has allocated one well with a designed depth of 3200 m and pressure coefficient of 2.3 in the Yinggehai Basin (called test well in the paper) in order to find gas reservoirs in middle-deep section in the Miocene Huangliu and Meishan formations at the depth below 3000 m. Therefore, combined with the '863' national high-tech project, the authors analyzed the distribution of overpressure in the Yinggehai and Qiongdongnan basins, and set up a series of key technologies and methods to predict and monitor formation pressure, and then apply the results to pressure prediction of the test well. Because of the exact pressure prediction before and during drilling, associated procedure design of casing and their allocation in test well has been ensured to be more rational. This well is successfully drilled to the depth of 3485 m (nearly 300 m deeper than the designed depth) under the formation pressure about 2.3 SG (EMW), which indicate that a new step in the technology of drilling in higher temperature and pressure has been reached in the China National Offshore Oil Corporation.
基金financially supported by the National Natural Science Foundation of China (grants No. 41772159/D0208, No. 41872178)the National Science and Technology Major Project of China (grant No. 2017ZX05064003)
文摘The main methods of coalbed methane(CBM)development are drainage and depressurization,and a precise prediction of coal reservoir pressure is thus crucial for the evaluation of reservoir potentials and the formulation of reasonable development plans.This work established a new reservoir pressure prediction model based on the material balance equation(MBE)of coal reservoir,which considers the self-regulating effects of coal reservoirs and the dynamic change of equivalent drainage area(EDA).According to the proposed model,the reservoir pressure can be predicted based on reservoir condition data and the actual production data of a single well.Compared with traditional reservoir pressure prediction models which regard EDA as a fixed value,the proposed model can better predict the average pressure of reservoirs.Moreover,orthogonal experiments were designed to evaluate the sensitivity of reservoir parameters on the reservoir pressure prediction results of this proposed model.The results show that the saturation of irreducible water is the most sensitive parameter,followed by Langmuir volume and reservoir porosity,and Langmuir pressure is the least sensitive parameter.In addition,the pressure drop of reservoirs is negatively correlated with the saturation of irreducible water and the Langmuir volume,while it is positively correlated with porosity.This work analyzed the reservoir pressure drop characteristics of the CBM wells in the Shizhuangnan Block of the Qinshui Basin,and the results show that the CBM reservoir depressurization can be divided into three types,i.e.,rapidly drop type,medium-term stability type,and slowly drop type.The drainage features of wells were reasonably interpreted based on the comprehensive analysis of the reservoir depressurization type;the latter was coupled to the corresponding permeability dynamic change characteristics,eventually proving the applicability of the proposed model.
基金funded by the Fundamental Research Program of MOST (No. 2015CB251201)the Scientific and Technological Innovation Project Financially Supported by Qingdao National Laboratory for Marine Science and Technology (No. 2016ASKJ13)the Natural Science Foundation of Hainan (No. ZDYF2016215)
文摘Overpressure in deepwater basins not only causes serious soft sediment deformation, but also significantly affects the safety of drilling operations. Therefore, prediction of overpressure in sediments has become an important task in deepwater oil exploration and development. In this study, we analyze the drilling data from ODP Leg 184 Sites 1144, 1146, and 1148, and IODP Leg 349 Sites U1431, U1432, U1433, and U1435 to study the sediment compaction and controls in the northern South China Sea. Sedimentation rate, sediment content, distribution area, and buried depth are the factors that influence sediment compaction in the deepwater basin of the South China Sea. Among these factors, the sediment content is the most important. The fitted normal compacted coefficients and mudline porosity for an interval of 50 m shows disciplinary variation versus depth. The pore pressure predicted from different fitted results shows varying overpressure situations. The normal compaction trend from Site 1144 reflects the porosity variation trend in stable deposition basins in the northern South China Sea. The predicted pore pressure shows overpressure at Site 1144, which is attributed to compaction disequilibrium. Nevertheless, the mixed lithology column may influence the predicted overpressure at Site 1148, which is responsible for the confusing result. Above all, we find that sediment compaction should serve as a proxy for pore pressure in the deepwater basin of the South China Sea.
文摘The basis of designing gasified drilling is to understand the behavior of gas/liquid two-phase flow in the wellbore. The equations of mass and momentum conservation and equation of fluid flow in porous media were used to establish a dynamic model to predict wellbore pressure according to the study results of Ansari and Beggs-Brill on gas-liquid two-phase flow. The dynamic model was solved by the finite difference approach combined with the mechanistic steady state model. The mechanistic dynamic model was numerically implemented into a FORTRAN 90 computer program and could simulate the coupled flow of fluid in wellbore and reservoir. The dynamic model revealed the effects of wellhead back pressure and injection rate of gas/liquid on bottomhole pressure. The model was validated against full-scale experimental data, and its 5.0% of average relative error could satisfy the accuracy requirements in engineering design.
文摘Pore pressure is an essential parameter for establishing reservoir conditions,geological interpretation and drilling programs.Pore pressure prediction depends on information from various geophysical logs,seismic,and direct down-hole pressure measurements.However,a level of uncertainty accompanies the prediction of pore pressure because insufficient information is usually recorded in many wells.Applying machine learning(ML)algorithms can decrease the level of uncertainty of pore pressure prediction uncertainty in cases where available information is limited.In this research,several ML techniques are applied to predict pore pressure through the over-pressured Eocene reservoir section penetrated by four wells in the Mangahewa gas field,New Zealand.Their predictions substantially outperform,in terms of prediction performance,those generated using a multiple linear regression(MLR)model.The geophysical logs used as input variables are sonic,temperature and density logs,and some direct pore pressure measurements were available at the reservoir level to calibrate the predictions.A total of 25,935 data records involving six well-log input variables were evaluated across the four wells.All ML methods achieved credible levels of pore pressure prediction performance.The most accurate models for predicting pore pressure in individual wells on a supervised basis are decision tree(DT),adaboost(ADA),random forest(RF)and transparent open box(TOB).The DT achieved root mean square error(RMSE)ranging from 0.25 psi to 14.71 psi for the four wells.The trained models were less accurate when deployed on a semi-supervised basis to predict pore pressure in the other wellbores.For two wells(Mangahewa-03 and Mangahewa-06),semi-supervised prediction achieved acceptable prediction performance of RMSE of 130—140 psi;while for the other wells,semi-supervised prediction performance was reduced to RMSE>300 psi.The results suggest that these models can be used to predict pore pressure in nearby locations,i.e.similar geology at corresponding depths within a field,but they become less reliable as the step-out distance increases and geological conditions change significantly.In comparison to other approaches to predict pore pressures,this study has identified that application of several ML algorithms involving a large number of data records can lead to more accurate prediction results.
文摘This article proposes a water inrush mechanism of progressive intrusion of pressure water up into the coal floor aquiclude according to injection tests and observations. A numerical model and a criterion of water inrush are established based on the mechanism. The theory is succesSfully used in predictions of water inrush.
文摘Yinggehai Basin locates in the northern South China Sea. Since the Cainozoic Era, crust has several strong tension: the basin subsides quickly, the deposition is thick, and the crust is thin. In the central basin, formation pressure coefficient is up to 2.1;Yinggehai Basin is a fomous high-temperature overpressure basin.YinggehaiBasin’s in-depth, especially high-temperature overpressure stratum has numerous large-scale exploration goals. As a result of high-temperature overpressure basin’s perplexing geological conditions and geophysical analysis technical limitations, this field of gas exploration can’t be carried out effectively, which affects the process of gas exploration seriously. A pressure prediction model of the high-temperature overpressure basin in different structural positions is summed up by pressure forecast pattern research in recent years, which can be applied to target wells pre-drilling pressure prediction and post drilling pressure analysis of Yinggehai Basin. The model has small erroneous and high rate of accuracy. The Yinggehai Basin A well drilling is successful in 2010, and gas is discovered in high-temperature overpressure stratum, which proved that reservoir can be found in high-temperature overpressure stratum. It is a great theoretical breakthrough of reservoir knowledge.
基金support of the National Natural Science Key Foundation of China(Grant Nos.91958206,91858215)the Key Research and Development Program of Shandong(Grant No.2019GHY112019)+2 种基金the China Sponsorship Council(Grant No.201806335026)the Opening Foundation of Key Lab of Submarine Geosciences and Prospecting Techniques,MOE,Ocean University of China(Grant No.SGPT-20210F-06)the Fundamental Research Funds for the Central Universities(Grant No.202161013)。
文摘The accurate prediction of formation pressure is important in oil/gas exploration and development.However,the achievement of this goal remains challenging,due to insufficient logging data and the low predictive data accuracy from seismic data.In this work,a case study was carried out in the Baima area of Wulong,in order to develop a workflow for accurately predicting shale gas formation pressure.The multi-channel stack method was first used,as well as the inversion of single-channel seismic data,to construct velocity and density models of the formation.Combined with the existing welllogging data,the velocity and density models of the whole well section were established.The shale gas formation pressure was then estimated using the Eaton method.The results show that the multi-channel seismic stacking method has a higher accuracy than the inversion of the formation velocity obtained by the single-channel seismic method.The discrepancies between our predicted formation pressure and the actual formation pressure measurement are within an acceptable range,indicating that our workflow is effective.
文摘The accurate prediction of overpressure is one of the key issues that restrict the effective development of oil and gas resources in the Yinggehai Basin. In this paper, the formation mechanism of overpressure in Yinggehai Basin is studied. Based on this mechanism, the quantitative prediction model and empirical parameters of overpressure are optimized in Yinggehai Basin and applied in engineering. The results show that the formation mechanism of overpressure in the Yinggehai Basin is complicated, and the causes of overpressure in different blocks of basin are different. The eastern block mainly develops loading-type overpressure, while the Ledong block is dominated by unloading high pressure. Different blocks should employ different abnormal high-pressure prediction models. The East block mainly adopts the Eaton method, and the Ledong block mainly utilizes the Bowers method. The empirical parameters of different models can be determined according to the actual drilling conditions. The practical application demonstrates that the abnormal high-pressure prediction error is within 2%, and it is able to satisfy the requirements of on-site engineering.
基金Projects(50805034, 50275035) supported by the National Natural Science Foundation of China
文摘The failure of AA3003 aluminum alloy sheet metal was predicted for non-isothermal viscous pressure bulging (VPB). Utilizing the coupled thermo-mechanical finite element method combined with ductile fracture criterion, the calculations were carried out for non-isotherm VPB at various temperatures and the influences of the initial temperature of viscous medium on failure mode of bulge specimens were investigated. The results show that the failure modes are different for the non-isothermal VPB with different initial temperatures of viscous medium. For the non-isothermal VPB of AA3003 aluminum alloy sheet with initial temperature of 250 ℃, when the initial temperature of viscous medium ranges from 150 to 180 ℃, the formability of sheet metal can be improved to a full extent. The validity of the predictions is examined by comparing with experimental results.