Analysis of Efficiency of Drilling of Large-Diameter Wells With a Profiled Wing Bit / Badania Efektywności Wiercenia Studni Wielkośrednicowych Świdrem Skrawającym z Profilowanymi Skrzydłami

2012 ◽  
Vol 57 (2) ◽  
pp. 363-373
Author(s):  
Jan Macuda
Keyword(s):  
Average Rate ◽  
Large Diameter ◽  
Open Pit ◽  
Mechanical Parameters ◽  
Drilling Rate ◽  
Geological Conditions ◽  
Rock Drillability ◽  
Drilling Technology ◽  
Weight On Bit ◽  
Rotary Speed

Abstract In Poland all lignite mines are dewatered with the use of large-diameter wells. Drilling of such wells is inefficient owing to the presence of loose Quaternary and Tertiary material and considerable dewatering of rock mass within the open pit area. Difficult geological conditions significantly elongate the time in which large-diameter dewatering wells are drilled, and various drilling complications and break-downs related to the caving may occur. Obtaining higher drilling rates in large-diameter wells can be achieved only when new cutter bits designs are worked out and rock drillability tests performed for optimum mechanical parameters of drilling technology. Those tests were performed for a bit ø 1.16 m in separated macroscopically homogeneous layers of similar drillability. Depending on the designed thickness of the drilled layer, there were determined measurement sections from 0.2 to 1.0 m long, and each of the sections was drilled at constant rotary speed and weight on bit values. Prior to drillability tests, accounting for the technical characteristic of the rig and strength of the string and the cutter bit, there were established limitations for mechanical parameters of drilling technology: P ∈ (Pmin; Pmax) n ∈ (nmin; nmax) where: Pmin; Pmax - lowest and highest values of weight on bit, nmin; nmax - lowest and highest values of rotary speed of bit, For finding the dependence of the rate of penetration on weight on bit and rotary speed of bit various regression models have been analyzed. The most satisfactory results were obtained for the exponential model illustrating the influence of weight on bit and rotary speed of bit on drilling rate. The regression coefficients and statistical parameters prove the good fit of the model to measurement data, presented in tables 4-6. The average drilling rate for a cutter bit with profiled wings has been described with the form: Vśr= Z ·Pa· nb where: Vśr- average drilling rate, Z - drillability coefficient, P - weight on bit, n - rotary speed of bit, a - coefficient of influence of weight on bit on drilling rate, b - coefficient of influence of rotary speed of bit on drilling rate. Industrial tests were performed for assessing the efficiency of drilling of large-diameter wells with a cutter bit having profiled wings ø 1.16 m according to elaborated model of average rate of drilling. The obtained values of average rate of drilling during industrial tests ranged from 8.33×10-4 to 1.94×10-3 m/s and were higher than the ones obtained so far, i.e. from 181.21 to 262.11%.

scholarly journals Sensitivity Analysis and 3D-displacement Inversion of Rock Parameters for High Steep Slope in Open-pit Mining

2016 ◽  
Vol 10 (1) ◽  
pp. 448-460 ◽  
Author(s):  
C.B. Zhou ◽  
R. He ◽  
N. Jiang ◽  
S.W. Lu
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Back Propagation ◽  
Back Analysis ◽  
Steep Slope ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mechanical Parameters ◽  
The Real ◽  
Geological Conditions

Due to the complexity of multiple rocks and multiple parameters circumstance, various parameters are often reduced to only one parameter empirically to generalize geological conditions, ignoring the really influential parameters. A developed method was presented as a complement to 3D displacement inversion to obtain the relative important parameters under complex conditions with limited computational work. Furthermore, this method was applied to a high steep slope in open-pit mining to investigate field applicability of the developed system. Back analysis was conducted in the reality of the east open-pit working area of Daye Iron Mine and propositional steps were presented for parameters solving in complex circumstance. Firstly, multi-factor and single-factor sensitivity analysis were carried out to classify rock mass and mechanical parameters respectively according to the extent of their effects on deformations. Secondly, based on the results, main influence factors were selected as inversion parameters and taken into a 3D calculating model to get the displacement field and stress field, all of which would be the artificial network training samples together with inversion parameters. Thirdly, taking the real deformations as input for the trained back propagation (BP) neural network, the real material mechanical parameters could be obtained. Finally, the results of trained neural network have been confirmed by field monitoring data and provide a reference to obtain the matter parameters in complicated environment for other similar projects.

Study on the Drilling Formation Selection and Risk Analysis of the Directional Drilling

2012 ◽  
Vol 461 ◽  
pp. 652-655
Author(s):  
Ying Wu ◽  
Peng Zhang ◽  
Xiao Li
Keyword(s):  
Site Investigation ◽  
Construction Site ◽  
Construction Process ◽  
Directional Drilling ◽  
Selection Methods ◽  
Related Literature ◽  
Literature Research ◽  
Geological Conditions ◽  
Drilling Technology ◽  
Pipeline Crossing

Directional drilling technology is an important and very promising trenchless pipeline crossing technology. On the basis of the related literature research at home and abroad and our pipeline construction site investigation, focuses on several common soil properties are introduced, and then the formation adaptability of directional drilling is analyzed. The drilling selection methods are made when drilling in the specific geological conditions, and the possible risks of the construction process have been classified in the directional drilling.

scholarly journals Substantiation of Safe Conditions During Undermining of Hydraulic Waste Disposal

2018 ◽  
Vol 41 ◽  
pp. 01007
Author(s):  
Yuriy Kutepov ◽  
Aleksandr Mironov ◽  
Maksim Sablin ◽  
Elena Borger
Keyword(s):  
Rock Mass ◽  
Waste Disposal ◽  
Coal Mine ◽  
Water Body ◽  
Water Inflow ◽  
Open Pit ◽  
Coal Seams ◽  
Geological Conditions ◽  
Mine Workings ◽  
Mine Dump

This article considers mining and geological conditions of the site “Blagodatny” of the mine named after A.D. Ruban located underneaththe old open pit coal mine and the hydraulic-mine dump. The potentially dangerous zones in the undermined rock mass have been identified based onthe conditions of formation of water inflow into mine workings. Safe depthof coal seams mining has been calculated depending on the type of water body – the hydraulic-mine dump.

scholarly journals On evaluation of complex-structured coal deposits based on their typical geometric features

2021 ◽  
Vol 303 ◽  
pp. 01029
Author(s):  
Alexander Katsubin ◽  
Victor Martyanov ◽  
Milan Grohol
Keyword(s):  
Surface Mining ◽  
Geological Structure ◽  
Point Of View ◽  
Open Pit ◽  
Open Pit Mining ◽  
Mining Operations ◽  
Coal Deposits ◽  
Geological Conditions ◽  
Wide Range ◽  
Large Length

Information about the geological structure of Kuznetsky coal basin (Kuzbass) allows us to note that coal deposits developed by open-cast method are characterized by complicated conditions and have the following features: large length of deposits at significant depths of occurrence; coal series bedding of different thicknesses (from 1 to 40 m); different dip angles (from 3 to 90º); a significant number of dip and direction disturbances; different thickness of unconsolidated quaternary sediments (from 5 to 40 m); a wide range of strength values of rocks. In addition, there is a thickness irregularity and frequent variability of elements of occurrence of coal seams within the boundaries of a quarry field both in length and depth of mining. From the point of view of open-pit mining, such deposits are complex-structured. The factors listed above have a decisive influence on the choice of technical means, the order of development and the possibility of carrying out surface mining operations. Therefore, there is a need for a systematization of mining and geological conditions for the development of coal deposits, the purpose of which is to ensure a process of evaluation of complex-structured coal deposits for the development of coal-bearing zones by various complexes of equipment.

scholarly journals The design of bottomhole assembly with two rock cutting tools for directional drilling

2018 ◽  
pp. 14-20
Author(s):  
I. V. Voievidko ◽  
V. V. Tokaruk ◽  
M. A. Bodzian
Keyword(s):  
Theoretical Analysis ◽  
Inclination Angle ◽  
Large Diameter ◽  
Cutting Tools ◽  
Intensity Variation ◽  
Rock Cutting ◽  
Hole Drilling ◽  
Directional Drilling ◽  
Geological Conditions ◽  
Technical Factors

On the basis of the theoretical analysis and practical studies of hole drilling of large diameter, a method for designing the BHA with two rock cutting tools is proposed, taking into account the geological and technical factors that have an impact on the formation of the trajectory. The calculation of BHA with two rock cutting tools and a different number of supporting and centralizing components for different geological conditions of drilling is carried out and the analysis of their work in the process of drilling is conducted. The graphic dependences of the deviation intensity variation and the inclination angle with the sinking of borehole of the large diameter for the BHA that can be used for the drilling of vertical and directional wells.

Stochastic Three-Dimensional Joint Geometry Model and the Properties of REV for a Jointed Rock Mass

2014 ◽  
Vol 1079-1080 ◽  
pp. 266-271
Author(s):  
Wen Hui Tan ◽  
Zhong Hua Sun ◽  
Ning Li ◽  
Xiao Hong Jiang
Keyword(s):  
Rock Mass ◽  
Probability Distributions ◽  
Three Dimensional ◽  
Jointed Rock ◽  
Jointed Rock Mass ◽  
Open Pit ◽  
Mechanical Parameters ◽  
Geometry Model ◽  
Joint Geometry ◽  
3D Network

The lithology of rock mass isnon-homogeneity，anisotropy, andexists size effect. The mechanical parameters of rock mass gotten by engineeringapproaches cannot reflect these properties. Therefore, a newmethod of determining the mechanical parameters of jointed rock mass isproposed: gneiss in Shuichang open-pit mine was selected as a case, thefracture system of the rock mass was measured and analyzed by non-contactmeasuring system of 3GSM and probabilisticmethod,the probability distributions of geometry parameters were analyzed and a 3Djoint geometry model was made by using the program of 3D network modeling.Cubes with different sizes were selected to be tested by tri-axial compressionof numerical simulation with 3DEC based on the 3D network model of joints,thus, the REV and its mechanical parameters were determined, which providedcredible parameters for slope stability analysis.

Drilling in the Digital Age: Machine Learning Assisted Bit Selection and Optimization

2021 ◽  
Author(s):  
Peter Batruny ◽  
Hafiz Zubir ◽  
Pete Slagel ◽  
Hanif Yahya ◽  
Zahid Zakaria ◽  
...  
Keyword(s):  
Machine Learning ◽  
Monte Carlo Analysis ◽  
Specific Model ◽  
Planning Decisions ◽  
Drilling Performance ◽  
Weight On Bit ◽  
Data Points ◽  
Ideal Tool ◽  
Rotary Speed ◽  
Artificial Neural Network Ann

Abstract Conventionally, a bit is selected from offset well bit run summaries. This method of selection is not always accurate since each bit is run under different conditions which might not be reflected in an offset study analysis. The large quantities of data generated from real time measurements in offset wells makes machine learning the ideal tool for analysis and comparison. Artificial Neural Network (ANN) is a relatively simple machine learning tool that combines inputs and calculation layers to compute a specified output layer. The ANN is fed over thousands of data points from 17-1/2 in hole sections across multiple wells. A specific model is then trained for every bit with weight on bit (WOB), rotary speed (RPM), bit hydraulics, and lithological properties as inputs and rate of penetration (ROP) as output. The model is finalized when a satisfactory statistical set of KPI's are achieved. Using a combination of Monte-Carlo analysis and sensitivity analysis, different bits are compared by varying parameters for the same bit and varying the bit under the same parameters. A bit and its optimized parameters are proposed, resulting in an average instantaneous ROP improvement of 32%. Performance benchmarked with individual drilling parameters shows improved ROP response to WOB, RPM, and bit hydraulics in the optimized run. This project solidifies machine learning as a powerful tool for bit selection and parameter optimization to improve drilling performance. Machine learning will become a significant part of well planning, design, and operations in the future. This study demonstrates how ANN's can be used to learn from previous operations and influence planning decisions to improve bit performance.

scholarly journals A Preliminary Study on the Design Method for Large-Diameter Deep-Hole Presplit Blasting and Its Vibration-Isolation Effect

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Shuangshuang Xiao ◽  
Hongsheng Wang ◽  
Guowei Dong
Keyword(s):  
Vibration Isolation ◽  
Design Method ◽  
Blast Hole ◽  
Large Diameter ◽  
Field Testing ◽  
Open Pit ◽  
Vibration Velocity ◽  
Deep Hole ◽  
Charge Mass ◽  
Presplit Blasting

Presplit blasting can reduce vibration and back impact induced by cast blasting, thus resulting in a smooth bench slope. To design reasonable presplit blasting parameters, this research investigated the formation of presplit faces based on the explosion mechanics and revealed the cracking mechanism of presplit blasting. According to the stress distribution in the vicinity of the blast holes under the action of explosive stress waves and blasting gas, we deduced theoretical formulae for parameters including charge mass in blast holes, hole spacing, and distance from presplit blast holes to cushion holes. On this basis, a method was proposed for the design of large-diameter deep-hole presplit blasting. Field testing was conducted by setting different spacing for presplit blast holes, to monitor the blasting-induced vibration. The results showed that appropriate hole spacing can reduce the particle vibration velocity and the attenuation index of blasting-induced vibration changed slightly while the attenuation coefficient decreased significantly; the formed presplit faces were smooth and had a high half-cast factor. Finally, the reasonable hole spacing for presplit blasting, distance from presplit blast hole to the cushion hole, and the charge mass in blast holes in the Heidaigou open-pit coal mine were determined, respectively.

Coal identification using neural networks with real-time coalbed methane drilling data

2019 ◽  
Vol 59 (1) ◽  
pp. 319 ◽  
Author(s):  
Ruizhi Zhong ◽  
Raymond Johnson Jr ◽  
Zhongwei Chen ◽  
Nathaniel Chand
Keyword(s):  
Real Time ◽  
Coalbed Methane ◽  
Gamma Ray ◽  
Ann Model ◽  
Drilling Data ◽  
Weight On Bit ◽  
Net To Gross ◽  
Rotary Speed ◽  
Artificial Neural Network Ann ◽  
Log Interpretation

Currently, coal is identified using coring data or log interpretation. Coring is the most dependable methodology, but it is costly and its characterisation is expensive and time consuming. Logging methods are convenient, reliable, and reproducible, but can be subject to statistical and shouldering effects and often have operational difficulties in deviated or horizontal wells. Drilling data, which are routinely available, can potentially be used to identify coal sections in a machine learning environment when conventional wireline logs are not available. To achieve this, a four-layer artificial neural network (ANN) was used to identify coals in a well at Walloon Sub-Group, Surat Basin. The ANN model used drilling data and some logging-while-drilling (LWD) data. The inputs for the lithological model from high-frequency drilling data include weight on bit, rotary speed, torque, and rate of penetration. Inputs from LWD data include gamma ray and hole diameter. The criterion for coal identification is based on bulk density cutoff. The simulation results show that the ANN can deliver an overall accuracy of 96%. Due to the low net-to-gross ratio of coals within the Walloon sequence, a lower but reasonable F1 score of 0.78 is achievable for the coal sections. The proposed model can potentially be implemented in real-time to identify coal intervals without additional logs and aid validation of minimal log data.

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