Data mining and well logging interpretation: application to a conglomerate reservoir

Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.

Intelligent and ecological coal mining as well as clean utilization technology in China: Review and prospects

Coal is an essential fossil fuel in China; however, coal mining and its utilization are being under the increasing pressure from ecological and environmental protection. Therefore, the consulting project "Technical Revolution in Ecological and Efficient Coal Mining and Utilization & Intelligence and Diverse Coordination of Coal-based Energy System," initiated by Chinese Academy of Engineering, puts forward three stages(3.0, 4.0 and 5.0) of China's coal industry development strategy. Aimed at "reduced staff,ultra-low ecological damage, and emission level near to natural gas," breakthroughs should be achieved in the following three key technologies during the China Coal Industry 3.0 stage(2016–2025): including intelligent coal mining, ecological mining, ultra-low emission and environmental protection. This paper focuses on the development trends of the China Coal Industry 3.0 and its support for China Coal Industry 4.0 and 5.0 is analyzed and prospected as well, which may offer technical assistance and strategy orientation for realizing the transformation from traditional coal energy to clean energy.

Production Characteristics and the Control Factors of Surface Wells for Relieved Methane Drainage in the Huainan Mining Area

Based on the production data of a large number of surface drainage wells in the Huainan mining area,the present study shows that four types of typical production characteristics for relieved methane wells are recognized,of which the stable type for production and gas concentration is the most dominate,as determined by a comprehensive study on the volume and concentration of drained gases, as well as the stress changes of rocks influenced by mining.Some influence factors for the productive differences of the drainage wells were also been discussed.The results indicate that protective coal-seam mining has a significant effect on overlying strata,which promotes the development of pores and fractures of coal reservoirs for methane desorption and migration;however,the production and the stability of drainage wells are affected by deformation and damage of the overlying strata.The second distribution of strata stress is caused by mining engineering,and if the stress load is larger than the carrying capacity of the extraction well,the gas production would be influenced by the drainage well that has been damaged by rock movement.Furthermore,the case damage occurs first in the weak, lithologic interface by its special mechanical properties.The stability of drainage wells and the production status are also influenced by the different drilling techniques,uneven distribution of gas concentration,and combination of gob gas and methane from the protected layer.

Exploitation technology of pressure relief coalbed methane in vertical surface wells in the Huainan coal mining area

Exploitation technology of pressure relief coalbed methane in vertical surface wells is a new method for exploration of gas and coalbed methane exploitation in mining areas with high concentrations of gas, where tectonic coal developed. Studies on vertical surface well technology in the Huainan Coal Mining area play a role in demonstration in the use of clean, new energy resources, preventing and reducing coal mine gas accidents and protecting the environment. Based on the practice of gas drainage engineering of pressure relief coalbed methane in vertical surface wells and combined with relative geological and exploration en- gineering theories, the design principles of design and structure of wells of pressure relief coalbed methane in vertical surface wells are studied. The effects of extraction and their causes are discussed and the impact of geological conditions on gas production of the vertical surface wells are analyzed. The results indicate that in mining areas with high concentrations of gas, where tectonic coal developed, a success rate of pressure relief coalbed methane in surface vertical well is high and single well production usually great. But deformation due to coal exploitation could damage boreholes and cause breaks in the connection between aquifers and bore-holes, which could induce a decrease, even a complete halt in gas production of a single well. The design of well site location and wellbore configuration are the key for technology. The development of the geological conditions for coalbed methane have a significant effect on gas production of coalbed methane wells.

Optimum location of surface wells for remote pressure relief coalbed methane drainage in mining areas

Based on engineering tests in the Huainan coal mining area,we studied alternative well location to improve the performance of surface wells for remote pressure relief of coalbed methane in mining areas.The key factors,affecting location and well gas production were analyzed by simulation tests for similar material.The exploitation results indicate that wells located in various positions on panels could achieve relatively better gas production in regions with thin Cenozoic layers,low mining heights and slow rate of longwall advancement,but their periods of gas production lasted less than 230 days,as opposed to wells in regions with thick Cenozoic layers,greater mining heights and fast rates of longwall advancement.Wells near panel margins achieved relatively better gas production and lasted longer than centerline wells.The rules of development of mining fractures in strata over panels control gas production of surface wells.Mining fractures located in areas determined by lines of compaction and the effect of mining are well developed and can be maintained for long periods of time.Placing the well at the end of panels and on the updip return airway side of panels,determined by lines of compaction and the effect of mining,would result in surface wells for remote pressure relief CBM obtaining their longest gas production periods and highest cumulative gas production.

Assessing risks from mining-induced ground movements near gas wells

The proliferation of unconventional gas well development in the Northern Appalachian coalfields has raised a number of mine safety concerns.Unconventional wells,which extract gas from deep shale formations,are characterized by gas volumes and pressures that are significantly higher than those observed at many conventional wells.The gas is composed largely of methane as well as other hydrocarbons.Hundreds of planned and actively producing wells penetrate protective coal pillars or barriers within active mine boundaries,including chain pillars located between longwall panels.Gas released from a well damaged by mining-induced ground movements could pose a risk to miners by flowing into the mine atmosphere.The mining-induced ground movements that may cause well damage include conventional subsidence,non-conventional subsidence(e.g.bedding plane slip),pillar failure,and floor instability.This paper describes the known risk factors for each of the four failure mechanisms.It includes a framework that can guide the risk assessment process when mining takes place near gas or oil wells.

Influence of longwall mining on the stability of gas wells in chain pillars

Longwall mining has a significant influence on gas wells located within longwall chain pillars.Subsurface subsidence and abutment pressure induced by longwall mining can cause excessive stresses and deformations in gas well casings.If the gas well casings are compromised or ruptured,natural gas could migrate into the mine workings,potentially causing a fire or explosion.By the current safety regulations,the gas wells in the chain pillars have to be either plugged or protected by adequate coal pillars.The current regulations for gas well pillar design are based on the 1957 Pennsylvania gas well pillar study.The study provided guidelines for gas well pillars by considering their support area and overburden depth as well as the location of the gas wells within the pillars.As the guidelines were developed for room-andpillar mining under shallow cover,they are no longer applicable to modern longwall coal mining,particularly,under deep cover.Gas well casing of failures have occurred even though the chain pillars for the gas wells met the requirements by the 1957 study.This study,conducted by the National Institute for Occupational Safety and Health(NIOSH),presents seven cases of conventional gas wells penetrating through longwall chain pillars in the Pittsburgh Coal Seam.The study results indicate that overburden depth and pillar size are not the only determining factors for gas well stability.The other important factors include subsurface ground movement,overburden geology,weak floor,as well as the type of the construction of gas wells.Numerical modeling was used to model abutment pressure,subsurface deformations,and the response of gas well casings.The study demonstrated that numerical models are able to predict with reasonable accuracy the subsurface deformations in the overburden above,within,and below the chain pillars,and the potential location and modes of gas well failures,thereby providing a more quantifiable approach to assess the stability of the gas wells in longwall chain pillars.

Failure characteristics of surface vertical wells for relieved coal gas and their influencing factors in Huainan mining area

Based on data from through-hole and logging,we studied the failure characteristics of surface drainage wells for relieved coal gas in Huainan mining area and its influencing factors.The results show that the damaged positions of drainage wells are mainly located at the thick clay layer in the low alluvium and the lithological interface in the upper section of bedrock in west mining area.The failure depth of casing is 244-670 m and concentrates at about 270-460 m deep.These damaged positions are mainly located in the bending zone according to three zones of rock layers in the vertical section above the roof divided. Generally,the casing begins to deform or damage before the face line about 30-150 m.Special formation structure and rock mass properties are the direct causes of the casing failure,high mining height and fast advancing speed are fundamental reasons for rock mass damage.However,the borehole configuration and spacing to the casing failure are not very clear.

Instability mechanism of mining roadway passing through fault at different angles in kilometre-deep mine and control measures of roof cutting and NPR cables

The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

The influence of inter-band rock on rib spalling in longwall panel with large mining height

In order to improve rib stability,failure criteria and instability mode of a thick coal seam with inter-band rock layer are analysed in this study.A three-dimensional mechanical model is established for the rib by considering the rock layer.A safety factor is defined foy the rib,and it is observed that the safety factor exhibits a positive correlation with the thickness and strength of the inter-band rock.A calculation method for determining critical parameters of the rock layer is presented to ensure the rib stability.It is revealed that incomplete propagation of the fracture at the hard rock constitutes a fundamental prerequisite for ensuring the rib stability.The influence of the position of the inter-band rock in the coal seam on failure mechanism of the rib was thoroughly investigated by developing a series of physical models for the rib at the face area.The best position for the inter-band rock in the coal seam is at a height of 1.5 m away from the roof line,which tends to provide a good stability state for the rib.For different inter-band rock positions,two ways of controlling rib by increasing supports stiffness and flexible grouting reinforcement are proposed.

Sustainable Mining in the Era of Artificial Intelligence

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

InSAR-derived surface deformation characteristics and mining subsidence parameters in mountain coal mines

Mining-induced surface deformation disrupts ecological balance and impedes economic progress.This study employs SBAS-InSAR with 107-view of ascending and descending SAR data from Sentinel-1,spanning February 2017 to September 2020,to monitor surface deformation in the Fa’er Coal Mine,Guizhou Province.Analysis on the surface deformation time series reveals the relationship between underground mining and surface shifts.Considering geological conditions,mining activities,duration,and ranges,the study determines surface movement parameters for the coal mine.It asserts that mining depth significantly influences surface movement parameters in mountainous mining areas.Increasing mining depth elevates the strike movement angle on the deeper side of the burial depth by 22.84°,while decreasing by 7.74°on the shallower side.Uphill movement angles decrease by 4.06°,while downhill movement angles increase by 15.71°.This emphasizes the technology's suitability for local mining design,which lays the groundwork for resource development,disaster prevention,and ecological protection in analogous contexts.

Introducing MagBERT:A language model for magnesium textual data mining and analysis

Magnesium(Mg)based materials hold immense potential for various applications due to their lightweight and high strength-to-weight ratio.However,to fully harness the potential of Mg alloys,structured analytics are essential to gain valuable insights from centuries of accumulated knowledge.Efficient information extraction from the vast corpus of scientific literature is crucial for this purpose.In this work,we introduce MagBERT,a BERT-based language model specifically trained for Mg-based materials.Utilizing a dataset of approximately 370,000 abstracts focused on Mg and its alloys,MagBERT is designed to understand the intricate details and specialized terminology of this domain.Through rigorous evaluation,we demonstrate the effectiveness of MagBERT for information extraction using a fine-tuned named entity recognition(NER)model,named MagNER.This NER model can extract mechanical,microstructural,and processing properties related to Mg alloys.For instance,we have created an Mg alloy dataset that includes properties such as ductility,yield strength,and ultimate tensile strength(UTS),along with standard alloy names.The introduction of MagBERT is a novel advancement in the development of Mg-specific language models,marking a significant milestone in the discovery of Mg alloys and textual information extraction.By making the pre-trained weights of MagBERT publicly accessible,we aim to accelerate research and innovation in the field of Mg-based materials through efficient information extraction and knowledge discovery.

Assessing trends in wildland-urban interface fire research through text mining: a comprehensive analysis of published literature

Research on fires at the wildland-urban inter-face(WUI)has generated significant insights and advance-ments across various fields of study.Environmental,agri-culture,and social sciences have played prominent roles in understanding the impacts of fires in the environment,in protecting communities,and addressing management challenges.This study aimed to create a database using a text mining technique for global researchers interested in WUI-projects and highlighting the interest of countries in this field.Author’s-Keywords analysis emphasized the dominance of fire science-related terms,especially related to WUI,and identified keyword clusters related to the WUI fire-risk-assessment-system-“exposure”,“danger”,and“vulnerability”within wildfire research.Trends over the past decade showcase shifting research interests with a growing focus on WUI fires,while regional variations highlighted that the“exposure”keyword cluster received greater atten-tion in the southern Europe and South America.However,vulnerability keywords have relatively a lower representation across all regions.The analysis underscores the interdisci-plinary nature of WUI research and emphasizes the need for targeted approaches to address the unique challenges of the wildland-urban interface.Overall,this study provides valu-able insights for researchers and serves as a foundation for further collaboration in this field through the understanding of the trends over recent years and in different regions.

Integrated biomarker response to assess toxic impacts of iron and manganese on deep-sea mussel Gigantidas platifrons under a deep-sea mining activity scenario

Deep-sea mining activities can potentially release metals,which pose a toxicological threat to deep-sea ecosystems.Nevertheless,due to the remoteness and inaccessibility of the deep-sea biosphere,there is insufficient knowledge about the impact of metal exposure on its inhabitants.In this study,deep-sea mussel Gigantidas platifrons,a commonly used deep-sea toxicology model organism,was exposed to manganese(100,1000μg/L)or iron(500,5000μg/L)for 7 d,respectively.Manganese and iron were chosen for their high levels of occurrence within deep-sea deposits.Metal accumulation and a battery of biochemical biomarkers related to antioxidative stress in superoxide dismutase(SOD),catalase(CAT),malondialdehyde(MDA);immune function in alkaline phosphatase(AKP),acid phosphatase(ACP);and energy metabolism in pyruvate kinase(PK)and hexokinase(HK)were assessed in mussel gills.Results showed that deep-sea mussel G.platifrons exhibited a high capacity to accumulate Mn/Fe.In addition,most tested biochemical parameters were altered by metal exposure,demonstrating that metals could induce oxidative stress,suppress the immune system,and affect energy metabolism of deep-sea mussels.The integrated biomarker response(IBR)approach indicated that the exposure to Mn/Fe had a negative impact on deep-sea mussels,and Mn demonstrated a more harmful impact on deep-sea mussels than Fe.Additionally,SOD and CAT biomarkers had the greatest impact on IBR values in Mn treatments,while ACP and HK were most influential for the low-and high-dose Fe groups,respectively.This study represents the first application of the IBR approach to evaluate the toxicity of metals on deep-sea fauna and serves as a crucial framework for risk assessment of deep-sea mining-associated metal exposure.

Experimental investigation of the inhibition of deep-sea mining sediment plumes by polyaluminum chloride

Deep-sea sediment disturbance may occur when collecting polymetallic nodules,resulting in the creation of plumes that could have a negative impact on the ecological environment.This study aims to investigate the potential solution of using polyaluminum chloride(PAC)in the water jet.The effects of PAC are examined through a self-designed simulation system for deep-sea polymetallic nodule collection and sediment samples from a potential deep-sea mining area.The experimental results showed that the optimal PAC dose was found to be 0.75 g/L.Compared with the test conditions without the addition of PAC,the presence of PAC leads to a reduction in volume,lower characteristic turbidity,smaller diffusion velocity,and shorter settling time of the plume.This indicates that PAC inhibits the entire development process of the plume.The addition of PAC leads to the flocculation of mm-sized particles,resulting in the formation of cm-sized flocs.The flocculation of particles decreases the rate of erosion on the seabed by around 30%.This reduction in erosion helps to decrease the formation of plumes.Additionally,when the size of suspended particles increases,it reduces the scale at which they diffuse.Furthermore,the settling velocity of flocs(around 10^(-2) m/s)is much higher that of compared to sediment particles(around 10^(-5) m/s),which effectively reduces the amount of time the plume remains in suspension.

A Quarterly High RFM Mining Algorithm for Big Data Management

In today’s highly competitive retail industry,offline stores face increasing pressure on profitability.They hope to improve their ability in shelf management with the help of big data technology.For this,on-shelf availability is an essential indicator of shelf data management and closely relates to customer purchase behavior.RFM(recency,frequency,andmonetary)patternmining is a powerful tool to evaluate the value of customer behavior.However,the existing RFM patternmining algorithms do not consider the quarterly nature of goods,resulting in unreasonable shelf availability and difficulty in profit-making.To solve this problem,we propose a quarterly RFM mining algorithmfor On-shelf products named OS-RFM.Our algorithmmines the high recency,high frequency,and high monetary patterns and considers the period of the on-shelf goods in quarterly units.We conducted experiments using two real datasets for numerical and graphical analysis to prove the algorithm’s effectiveness.Compared with the state-of-the-art RFM mining algorithm,our algorithm can identify more patterns and performs well in terms of precision,recall,and F1-score,with the recall rate nearing 100%.Also,the novel algorithm operates with significantly shorter running times and more stable memory usage than existing mining algorithms.Additionally,we analyze the sales trends of products in different quarters and seasonal variations.The analysis assists businesses in maintaining reasonable on-shelf availability and achieving greater profitability.

Experimental investigation of dynamic characteristics of leaching tubing for solution mining of salt cavern carbon and energy storage

Salt caverns are extensively utilized for storing various substances such as fossil energy,hydrogen,compressed air,nuclear waste,and industrial solid waste.In China,when the salt cavern is leached through single-well water solution mining with oil as a cushion,engineering challenges arise with the leaching tubing,leading to issues like damage and instability.These problems significantly hinder the progress of cavern construction and the control of cavern shape.The primary cause of this is the flowinduced vibration instability of leaching tubing within a confined space,which results in severe bending or damage to the tubing.This study presents a model experimental investigation on the dynamic characteristics of leaching tubing using a self-developed liquid-solid coupling physical model experiment apparatus.The experiment utilizes a silicone-rubber pipe(SRP)and a polycarbonate pipe(PCP)to examine the effects of various factors on the dynamic stability of cantilevered pipes conveying fluid.These factors include external space constraint,flexural rigidity,medium outside the pipe,overhanging length,and end conditions.The experiments reveal four dynamic response phenomena:water hammer,static buckling,chaotic motion,and flutter instability.The study further demonstrates that the length of the external space constraint has a direct impact on the flutter critical flow velocity of the cantilevered pipe conveying fluid.Additionally,the flutter critical flow velocity is influenced by the end conditions and different external media.

Game theory attack pricing for mining pools in blockchain-based IoT

The malicious mining pool can sacrifice part of its revenue to employ the computing power of blockchain network.The employed computing power carries out the pool mining attacks on the attacked mining pool.To realize the win-win game between the malicious mining pool and the employee,the paper proposes an Employment Attack Pricing Algorithm(EAPA)of mining pools in blockchain based on game theory.In the EAPA,the paper uses mathematical formulas to express the revenue of malicious mining pools under the employment attack,the revenue increment of malicious mining pools,and the revenue of the employee.It establishes a game model between the malicious mining pool and the employee under the employment attack.Then,the paper proposes an optimal computing power price selection strategy of employment attack based on model derivation.In the strategy,the malicious mining pool analyzes the conditions for the employment attack,and uses the derivative method to find the optimal utilization value of computing power,employees analyze the conditions for accepting employment,and use the derivative method to find the optimal reward value of computing power.Finally,the strategy finds the optimal employment computing power price to realize Nash equilibrium between the malicious mining pool and the employee under the current computing power allocation.The simulation results show that the EAPA could find the employment computing power price that realizes the win-win game between the malicious mining pool and the employee.The EAPA also maximizes the unit computing power revenue of employment and the unit computing power revenue of honest mining in malicious mining pool at the same time.The EAPA outperforms the state-of-the-art methods such as SPSUCP,DPSACP,and FPSUCP.