Research progress and application of deep in-situ condition preserved coring and testing

With the depletion of shallow resources,the exploration of deep earth resources has become a global strategy.The study of the different patterns in the physical mechanical properties of rocks at different occurrence depths is the basis for exploring deep into the earth,with the core and premise being the acquisition and testing of deep in-situ core specimens.Based on the original idea of deep in-situ condition preserved coring(ICP-Coring)and testing,combined with theoretical modeling,numerical analysis,test platform development,indoor testing and engineering application,the principles and technologies of deep ICP-Coring are developed.This principle and technology consists of five parts:in-situ pressurepreserved coring(IPP-Coring),in-situ substance-preserved coring(ISP-Coring),in-situ temperaturepreserved coring(ITP-Coring),in-situ light-preserved coring(ILP-Coring),and in-situ moisturepreserved coring(IMP-Coring).The theory and technology of temperature and pressure reconstruction at different occurrence depths and in different environments are proposed,and prototype trial production was completed by following the principle of displacement and tests based on the in-situ reconstructed environment.The notable advances are as follows:(1)Deep in-situ coring system:A pressure-preserved controller with an ultimate bearing capacity greater than 140 MPa,highperformance(temperature-resistant,pressure-resistant,and low thermally conductive)temperaturepreserved materials,an active temperature control system,and high-barrier quality-preserved membrane materials were developed;a deep ICP-Coring capacity calibration platform was independently developed,a deep in-situ coring technology system was developed,and the acquisition of deep in-situ cores was realized.(2)In-situ storage displacement system:Following the dual-circuit hydraulic design idea,a single-drive source push-pull composite grabbing mechanism was designed;the design of the overall structure for the deep in-situ displacement storage system and ultrahigh pressure cabin structure was completed,which could realize docking the coring device and core displacement in the in-situ reconstructed environment.(3)Test analysis system:A noncontact acoustic-electric-magnetic test system was developed under the in-situ reconstructed environment,and the errors between the test results and traditional contact test results were mostly less than 10%;a detachable deep in-situ core true triaxial test system was developed,which could perform loading tests for deep in-situ cores.The relevant technological achievements were successfully applied to the exploration and development of deep resources,such as deep mines,deep-sea natural gas hydrates,and deep oil and gas.The research results provide technical and equipment support for the construction of a theoretical system for deep in-situ rock mechanics,the development of deep earth resources and energy,and the scientific exploration of different layers and occurrence depths(deep and ultradeep)of the Earth.

Study on Load Bearing Characteristics of Novel Expandable Deepwater Drilling Conductor Based on Laboratory Experiment and Field Test

A novel expandable conductor was designed and applied in deep-water drilling to improve the vertical and lateral bearing capacity with a significant reduction of conductor jetting depth and soaking time. The vertical and lateral bearing capability of expandable conductors was depicted based on the ultimate subgrade reaction method and pile foundation bearing theory. The load-bearing characteristics of a laboratory-scale expandable conductor were analyzed through laboratory experiments. The serial simulation experiments are accomplished to study the bearing characteristics(vertical ultimate bearing capacity, lateral soil pressure, and lateral displacement) during the conductor soaking process. The laboratory experimental results show that the larger the length and thickness of expandable materials are,the higher the bearing capacity of the wellhead will be. During the conductor soaking process, the soil pressure around the three expandable conductors increases faster, strings representing a stronger squeezing effect and resulting in higher vertical bearing capacity. Furthermore, the lateral displacement of novel expandable conductor is smaller than that of the conventional conductor. All the advantages mentioned above contributed to the reduction of conductor’s jetting depth and soaking time. Lastly, the application workflow of a novel expandable deep-water drilling conductor was established and the autonomous expandable conductor was successfully applied in the South China Sea with a significant reduction of conductor’s jetting depth and soaking time. According to the soil properties and designed installation depth of the surface conductor, the arrangement of expandable materials should be designed reasonably to meet the safety condition and reduce the construction cost of the subsea wellhead.

A thermal stress loading technique for large-sized hot dry rock mechanical tests

Testing of large-sized specimens is becoming increasingly important in deep underground rock mechanics and engineering.In traditional mechanical loading,stresses on large-sized specimens are achieved by large host frames and hydraulic pumps,which could lead to great investment.Low-cost testing machines clearly always have great appeal.In this study,a new approach is proposed using thermal expansion stress to load rock specimens,which may be particularly suitable for tests of deep hot dry rock with high temperatures.This is a different technical route from traditional mechanical loading through hydraulic pressure.For the rock mechanics test system of hot dry rock that already has an investment in heating systems,this technology may reduce the cost of the loading subsystem by fully utilizing the temperature changes.This paper presents the basic principle and a typical design of this technical solution.Preliminary feasibility analysis is then conducted based on numerical simulations.Although some technical details still need to be resolved,the feasibility of this loading approach has been preliminarily confirmed.

Non-destructive testing and pre-warning analysis on the quality of bolt support in deep roadways of mining districts

The bolt support quality of coal roadways is one of the important factors for the efficiency and security of coal production. By means of a self-developed technique and equipment of random non-destructive testing, non-destructive detection and pre-warning analysis on the quality of bolt support in deep roadways of mining districts were performed in a number of mining areas. The measured data were obtained in the detection instances of abnormal in-situ stress and support invalidation etc. The corresponding relation between axial bolt load variation and roadway surrounding rock deformation and stability was summarized in different mining service stages. Pre-warning technology of roadway surrounding rock stability is proposed based on the detection of axial bolt load. Meanwhile, pre-warning indicators of axial bolt load in different mining service stages are offered and some successful pre-warning cases are also illustrated.The research results show that the change rules of axial bolt load in different mining service stages are quite similar in different mining areas. The change of axial bolt load is in accord with the adjustment of surrounding rock stress, which can consequently reflect the deformation and stability state of roadway surrounding rock. Through the detection of axial bolt load in different sections of roadways, the status of real-time bolt support quality can be reflected; meanwhile, the rationality of bolt support design can be evaluated which provides reference for bolting parameters optimization.

Field testing of stiffened deep cement mixing piles under lateral cyclic loading

Construction of seaside and underground wall bracing often uses stiffened deep cement mixed columns （SDCM）. This research investigates methods used to improve the level of bearing capacity of these SDCM when subjected to cyclic lateral loading via various types of stiffer cores. Eight piles, two deep cement mixed piles and six stiffened deep cement mixing piles with three different types of cores, H shape cross section prestressed concrete, steel pipe, and H-beam steel, were embedded though soft clay into medium-hard clay on site in Thailand. Cyclic horizontal loading was gradually applied until pile failure and the hysteresis loops of lateral load vs. lateral deformation were recorded. The lateral carrying capacities of the SDCM piles with an H-beam steel core increased by 3-4 times that of the DCM piles. This field research clearly shows that using H-beam steel as a stiffer core for SDCM piles is the best method to improve its lateral carrying capacity, ductility and energy dissipation capacity.

Application of bi-directional static loading test to deep foundations

Bi-directional static loading test adopting load cells is widely used around the world at present, with increase in diameter and length of deep foundations. In this paper, a new simple conversion method to predict the equivalent pile head load-settlement curve considering elastic shortening of deep foundation was put forward according to the load transfer mechanism. The proposed conversion method was applied to root caisson foundation in a bridge and to large diameter pipe piles in a sea wind power plant. Some new load cells, test procedure, and construction technology were adopted based on the applications to different deep foundations, which could enlarge the application scopes of bi-directional loading test. A new type of bi-directional loading test for pipe pile was conducted, in which the load cell was installed and loaded after the pipe pile with special connector has been set up. Unlike the conventional bi-directional loading test, the load cell can be reused and shows an evident economic benefit.

A deep reinforcement learning(DRL)based approach for well-testing interpretation to evaluate reservoir parameters

Parameter inversions in oil/gas reservoirs based on well test interpretations are of great significance in oil/gas industry.Automatic well test interpretations based on artificial intelligence are the most promising to solve the problem of non-unique solution.In this work,a new deep reinforcement learning(DRL)based approach is proposed for automatic curve matching for well test interpretation,by using the double deep Q-network(DDQN).The DDQN algorithms are applied to train agents for automatic parameter tuning in three conventional well-testing models.In addition,to alleviate the dimensional disaster problem of parameter space,an asynchronous parameter adjustment strategy is used to train the agent.Finally,field applications are carried out by using the new DRL approaches.Results show that step number required for the DDQN to complete the curve matching is the least among,when comparing the naive deep Q-network(naive DQN)and deep Q-network(DQN).We also show that DDQN can improve the robustness of curve matching in comparison with supervised machine learning algorithms.Using DDQN algorithm to perform 100 curve matching tests on three traditional well test models,the results show that the mean relative error of the parameters is 7.58%for the homogeneous model,10.66%for the radial composite model,and 12.79%for the dual porosity model.In the actual field application,it is found that a good curve fitting can be obtained with only 30 steps of parameter adjustment.

Zonal disintegration test of deep tunnel under plane strain conditions

To investigate the zonal disintegration form of the surrounding rock in deep tunnels,model tests were performed in the simulation set-up of fracture mechanism and support technology of surrounding rock in deep tunnel.The test results illustrate that the first fracture of the surrounding rock occurred at the intersection of the tunnel floor and the side wall.After more serious destruction,the side wall and the vault were destroyed.Although the fracture width of each surrounding rock mass was distinct,they were relatively uniform with a nearly continuous fracture form.The width of the split bodies of the model tunnels(i.e.,the annular zonal disintegration area)developed with an increasing load.It was observed from the fitting curves of the data that all radial strain values of the surrounding rock were more symmetric with a smooth fitting curve,and the maximum value occurred near the tunnel wall before reducing instantly.The circumferential strain values were dispersed and the data were inconsistent with the fitting curve,which caused some data to be unreliable.The phenomenon of zonal disintegration was primarily caused by radial tension strain of the surrounding rock.This phenomenon would not extend indefinitely as the rupture range would be limited to a certain extent,because the maximum radial tension strain of the surrounding rock was less than the limiting value.

Analysis and seismic tests of composite shear walls with CFST columns and steel plate deep beams

A composite shear wall concept based on concrete filled steel tube （CFST） columns and steel plate （SP） deep beams is proposed and examined in this study. The new wall is composed of three different energy dissipation elements： CFST columns; SP deep beams; and reinforced concrete （RC） strips. The RC strips are intended to allow the core structural elements - the CFST columns and SP deep beams - to work as a single structure to consume energy. Six specimens of different configurations were tested under cyclic loading. The resulting data are analyzed herein. In addition, numerical simulations of the stress and damage processes for each specimen were carried out, and simulations were completed for a range of location and span-height ratio variations for the SP beams. The simulations show good agreement with the test results. The core structure exhibits a ductile yielding mechanism characteristic of strong column-weak beam structures, hysteretic curves are plump and the composite shear wall exhibits several seismic defense lines. The deformation of the shear wall specimens with encased CFST column and SP deep beam design appears to be closer to that of entire shear walls. Establishing optimal design parameters for the configuration of SP deep beams is pivotal to the best seismic behavior of the wall. The new composite shear wall is therefore suitable for use in the seismic design of building structures.

Prediction of wax precipitation region in wellbore during deep water oil well testing

During deep water oil well testing, the low temperature environment is easy to cause wax precipitation, which affects the normal operation of the test and increases operating costs and risks. Therefore, a numerical method for predicting the wax precipitation region in oil strings was proposed based on the temperature and pressure fields of deep water test string and the wax precipitation calculation model. And the factors affecting the wax precipitation region were analyzed. The results show that: the wax precipitation region decreases with the increase of production rate, and increases with the decrease of geothermal gradient, increase of water depth and drop of water-cut of produced fluid, and increases slightly with the increase of formation pressure. Due to the effect of temperature and pressure fields, wax precipitation region is large in test strings at the beginning of well production. Wax precipitation region gradually increases with the increase of shut-in time. These conclusions can guide wax prevention during the testing of deep water oil well, to ensure the success of the test.

Hydrocarbon test in lower-layer atmosphere to predict deep-sea petroleum or hydrate in the Okinawa Trough: an example

Light hydrocarbon (methane, ethane, propane, butane and CO2) test and C isotopic analysis of CO are conducted for over 100 lower-layer atmospheric samples from the East China Sea slope and the Okinawa Trough. The results show that the lower-layer atmosphere mainly consists of CO2 and then of CH4, and the CO2 concentrations are calculated to have a high average value of 0.87 omega/10(-2) about three times that of the regional background (0-3 omega/10(-2)). The result also shows that the average value of C isotope - 20.8 x 10(-3) is given to the CO2, inferring that it is inorganic gas. Thus, for the future 's work in the Okinawa Trough, special attention should be paid to CO2 hydrate, which is very possibly an important hydrate type.

Mechanical Properties of Deep-buried Marble Material Under Loading and Unloading Tests

The mechanical properties are essentially different when rock material is subjected to loading or unloading conditions. In this study, loading and unloading tests with various confining pressures are conducted to investigate the mechanical properties of marble material samples taken from the deep diversion tunnels of Jinping II Hydropower Station. The stress-strain relationship, failure characteristics and strength criterion are compared and analyzed based on the experiment results. The results show： in the loading and unloading test, peak strength, lateral strain, axial strain and plastic deformation increase significantly as the confining pressure increases. Lateral strain increased significantly and obvious lateral dilatancy can be observed to the change of confining pressure; The fracture mode is mainly the single shear fracture for the triaxial compression test and post-peak test, angle between the failure surface and the ends of the rock material becomes smaller as the confining pressure increases. Hock-Brown strength criterion reflects the strength characteristics of marble material under two different unloading conditions, and has some supplementary effects to the rock material of mechanical field.

Young footballers, assessed by deep breathing test, have a higher vagal response

Parasympathetic function can be assessed by the deep breathing test (DB) as a simple and reproducible cardiovascular reflex. The aim of this study is to use this test to compare the vagal response of a young footballers group to of age-matched untrained normal subjects. Deep breathing test was performed in 2 groups: one of 20 adult young footballers (average age of 19.3 ± 0.6 years), and a second age-matched group of 20 untrained subjects (average age of 19.6 ± 0.6 years). Subjects underwent the DB test after 30 min resting in supine position, and responses were expressed as a percentage of variation of heart rate during the stimulation. Student’s t-test was used to evaluate statistical differences among the two groups for all parameters (vagal response, heart rate, VO2max….) and considering p < 0.05 as a significant difference. The results showed that vagal response to deep breathing test was significantly higher in the young footballers when compared to the untrained controls (72.6% ± 16.2% vs 55.0% ± 12.8%, respectively, p = 0.03). The basal heart rate was significantly lower in footballers than in the controls group (52.1 ± 7.4 bat/min vs 69.8 ± 14.3 bat/min, p < 0.01). The use of the simple test of deep breathing allowed us to demonstrate that adult young footballers have a significantly lower basal HR and higher parasympathetic response in comparison to untrained subjects.

DeepRanger:覆盖制导的深度森林测试方法

深度学习软件的结构特征与传统软件存在明显差异,因此即使展开了大量测试,依然无法有效衡量测试数据对深度学习软件的覆盖情况和测试充分性,并造成后续使用过程中依然可能存在大量未知错误.深度森林是一种新型深度学习模型,其克服了深度神经网络存在的一些缺点,例如:需要大量训练数据、需要高算力平台、需要大量超参数.但目前还没有相关工作对深度森林的测试方法进行研究.针对深度森林的结构特点,制定了一组由随机森林结点覆盖率RFNC、随机森林叶子覆盖率RFLC、级联森林类型覆盖率CFCC和级联森林输出覆盖率CFOC组成的测试覆盖率评价指标.在此基础上,基于遗传算法设计了覆盖制导的测试数据自动生成方法DeepRanger,可自动生成能有效提高模型覆盖率的测试数据集.为对所提出覆盖指标的有效性进行验证,在深度森林开源项目gcForest和MNIST数据集上设计并进行了一组实验.实验结果表明,所提出的4种覆盖指标均能有效评价测试数据集对深度森林模型的测试充分性.此外,与基于随机选择的遗传算法相比,使用覆盖信息制导的测试数据生成方法DeepRanger能达到更高的模型覆盖率.

Towards Integrated Testing Approach: An Application of Cognitive Science and Deep Learning Principle

The use of multiple-choice(MC)question types has been one of the most contentious issues in language testing.Much has been said and written about the use of MC over the years.However,no attempt has ever been made to introduce any innovation in test item types.The researchers proposed a jumbled words test item(JW)based on cognitive science and deep learning principles,and addressed the feasibility of replacing the type of multiple-choice(MC)question with JW to meet the ongoing rapid development of language testing practice.Two research questions were proposed ad hoc,focusing on the co-relationship between JW and MC scores.RASCH-GZ was used to perform item analyses(Rasch,1960).The item difficulty parameters thus obtained were used to compare the two different test items.The sample data metric includes 40 Chinese participants.The findings revealed that correlation analysis revealed that the performance of the same group of subjects taking both JW and MC was not relevant(Pearson Corr=0).This is primarily due to the total elimination of guessing factors inherent in test-takers during JW test performance.Three factors were specified for the design of the JW test:compute program,test difficulty,and score acceptability.These all have three dimensions.Data collected through questionnaires were analyzed using EFA in SPSS V.24.0.KMOs(=0.867)were found to be approximately one and significance at 0.000(0.05),indicating that the construct of theuestionnaire thus designed has better validity for factor analysis.Three important conclusions were obtained,the implications of which could provide impetus for our testing counterparts to practice more precisely and correctly,potentially reshaping our overall language testing practice.Limitations and recommendations for future research were also discussed.

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around.Hence,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield.In present decade,the application of deep learning models in many fields of research has created greater impact.The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil quality.With that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil quality.Firstly,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)model.Secondly,soil nutrient data has been given as second input to the DNNR model.By utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been estimated.For training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the dataset.The results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification accuracy.The results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

Reasons resulting in the collapsed tubing near wellhead in high pressure and high temperature deep well during well testing and measures to prevent the collapsing

Because various reasons, the tubing near wellhead was collapsed during well testing in high pressure and high temperature deep well when the outer pressure was less than collapsing strength. To find the reasons in the abnormally collapse and countermeasures, first the quality of the tubing was checked. It was founded that the collapse was not resulted from the defect of the tubing. Then, force and stress exerted in the tubing was analyzed taking XS2 well as an example. The analysis results were concluded as follows. The collapsing strength of tubing decreased due to the axial tensile, which is seriously at the upper tubing especially. During injecting, the additional axial force that was caused by the temperature effect increased the tubing near wellhead to suffer axial tensile and further reduced the collapsing strength of tubing near wellhead. Reinforcing defect, prohibiting defect tubing to trip in hole, according to the calculation to impose appropriate annular pressure, selecting size nozzle to reverse pumping and controlling the reverse pumping speed and pressure, prohibiting to be opened flow and reducing or releasing the annular pressure can prevent the well testing tubing down-hole being collapsed at the wellhead.

稠油化学复合冷采技术研究与应用

我国稠油储量可观,其中60%的是深层稠油,而主流的蒸汽吞吐等热采技术采收率不足20%;稠油资源开发潜力极大,积极探索新的开采方式以提高采收率是石油领域高质量发展的必然选择。本文着重阐述稠油化学复合冷采技术体系构建及其现场应用,为中深层稠油的新型绿色低成本接替技术发展提供有效方案。在分析稠油组分的基础上,细致剖析稠油结构致黏机理,包括化学降黏机理、降低启动压力梯度机理、提高驱油效果机理在内的提高采收率机理,以丰富理论认识。面向工程应用亟需,从水溶性降黏剂分子设计与合成、自组装调堵剂研发两方面出发,突破稠油绿色化学驱油体系。基于发展的稠油化学复合冷采技术,完成了3个稠油油田示范工程应用,在提高产油量、控制含水率方面取得了良好成效。进一步梳理了分子采油理论与技术、渗流理论与数值模拟技术等方面的后续发展要点,以为深层稠油的绿色高效开发接替技术研究、稠油化学复合冷采技术推广应用研究等提供启发和参考。

深海环境腐蚀试验技术及研究进展

从深海实海环境试验、模拟试验、原位电化学测试、数值仿真等方面阐述了深海环境试验技术的发展演变过程。介绍了国内外主要深海腐蚀研究使用的试验装置种类,各类装置的优缺点和使用场景,并以试验装置为平台,发展了金属材料深海原位电化学测试技术及深海测试数据实时远程传输技术。介绍了实验室模拟深海环境腐蚀试验技术由单因素模拟到多因素模拟,并结合力学及实时测试的发展历程。阐述了数值仿真技术在深海环境腐蚀研究方面的应用,推介了2项ISO深海环境试验方法国际标准,回顾了近期在材料深海环境腐蚀研究方面取得的最新成果。面向深海装备应用的需求,从新试验技术发展出发,探讨了深海试验技术研究的发展方向和趋势。

基于串并行双分支网络的冲击波信号重构方法

通过有限测点数据重建冲击波场内压力分布、通过残缺数据重构完整的冲击波压力曲线,对武器威力以及目标毁伤评估具有重要价值。针对爆炸冲击波信号重构问题,建立Res-GRU分支以串行方式捕捉冲击波超压信号局部时序依赖关系;建立Transformer分支以并行方式分析信号全局潜在特征;建立特征融合单元进行高阶特征融合,实现不同阶段信息逐层互补;进而构建了基于门控循环单元(gated recurrent unit,GRU)和Transformer模型的串并行双分支网络(G-TNet)。试验研究表明:G-TNet综合考量了信号的时序关系、数据变化规律等特征信息;在基于有限测点数据的冲击波场压力分布重构试验中,重建的模拟、实测超压数据与原始值之间均方误差(mean square error,MSE)分别为5.0×10^(-6)、1.2×10-3,平均峰值误差分别为0.49%、27.01%,平均正压时间误差分别为15.62%、15.91%,平均比冲量误差分别为17.66%、19.33%;在基于残缺数据的冲击波压力曲线重构试验中,重构的模拟、实测信号的缺失值与原始值之间MSE分别为5.0×10^(-6)和5.0×10^(-4),平均绝对误差(mean absolute error,MAE)分别为0.0010和0.0171;G-TNet重构结果优于主流方法,满足爆炸冲击波压力重构指标要求。