Drill-hole spacing optimization for profit in grade control

Geostatistical conditional simulation has wide potential applications in the iron ore industry and is the favoured tool to assess variability and risk. Multivariate relationships are important in such simulation, for example between Fe and impurities such as Al2O3, SiO2 and P. Turning bands has been the main conditional simulation algorithm used in the Western Australian iron ore industry. In this thesis a more recent approach using minimum/maximum autocorrelation factors (MAF) and sequential Gaussian simulation (SGS) are used together and performance comparisons are made with turning bands at Yandicoogina, a channel iron ore deposit (CID) in Western Australia. MAF-SGS and turning bands algorithms both performed well in simulating Fe, SiO2, Al2O3 and P at Yandicoogina. Extensive checking of simulations showed both approaches could reasonably reproduce multivariate statistics and spatial continuity of composites including means, variances, histograms, quantile-quantile plots, scatter plots and variography in normal scores and data space, as well as in MAF space for the MAFSGS approach. MAF generated from transformed composites were largely uncorrelated and able to be considered independent for variography and simulation. Later back transformation from MAF space to normal scores space then to data space successfully reintroduced joint relationships seen in the conditioning data. While the MAF-SGS approach needs additional transformations compared with turning bands, a linear model of coregionalisation and hence the modelling of cross semivariograms is not required. If there are a high number of variables then construction of a linear model of coregionalisation becomes more difficult and the MAF approach may be preferred. In this study four variables were considered and a linear model of coregionalisation could be built. Turning bands transformations are from data space to normal scores space only, with no need to calculate or check any decorrelated factors. The two main methods currently used in the mining industry for determining optimum drillhole spacing with the use of conditional simulation were compared at the Test Pit area of the Bungaroo channel iron ore deposit, also in Western Australia. The method generates precisions for various drillhole spacing using two stages of simulation, whereas the approach calculates expected relative errors for different spacings via a simulation stage followed by an estimation step. Clear differences exist between the relative errors from the simulation-estimation method and the precisions calculated from the simulation-simulation method. The simulationestimation method appears more insensitive to the grid spacing with only moderate improvements in relative error as the drillhole spacing is tightened. The simulationsimulation method shows more marked improvement in precision with closer spacing and appears more realistic in this study. Al2O3 is the main variable to consider at Bungaroo when choosing a suitable drillhole spacing. SiO2 grades of composites are mainly below the SiO2 cut off grade for ore whereas the mean Al2O3 is grade is quite close to the Al2O3 cut off grade for ore. Hence although SiO2 has higher variability, it is not as critical as Al2O3 for determination of drillhole spacing. Fe and P have greater spatial continuity than Al2O3 and SiO2 and do not require such close drillhole spacing. Fifteen percent precision, based on a volume representing a quarter’s production and using the simulation-simulation method, may be regarded as acceptable for mine planning purposes. A resource evaluation drilling spacing of 150m along strike and 50m across strike appears appropriate for a precision of less than 15% for a quarterly mining volume in determining Al2O3 grade at Bungaroo.

Drill hole spacing optimization of non-stationary data for seam thickness and total sulfur: A case study of coal deposits at Balikpapan Formation, Kutai Basin, East Kalimantan

The research work results, presented in the article, describe a system concerning the management of a production line in the aspect of stabilization and improvement of the run-of-mine quality and maximization of economic effects. Basing on the geological deposit model, the authors concentrated on designing mining operations and on planning production parameters. Special attention was paid to a development of the mine workings design module, the mining operations scheduling module, the module for mixing and optimization from the quality point of view as well as the module for mining operations revenues and forecasts of costs. Forecasting the production quality, planning and integration of mining processes with coal preparation processes and sales are discussed in detail. The article is ended with some recommendations of general character, including quality management at the stage of mining and production planning, quality monitoring at the stage of coal mining, and its preparation. The system is oriented onto production quality forecasting and onto an integration of mining, preparation and sales planning.

In detailed exploration, it is necessary to analyze optimal drill hole distance. Drill hole spacing analysis results in optimal drill hole spacing on each coal seam for the coal resources classification. Based on a case study in one of the coal mining companies in North Bengkulu, four coal seams have continuous seams and there is splitting from one seam to four seams. The sediment model generally has a direction of distribution of coal seams trending from northeast to southwest with gentle dip. This research uses geostatistical methods to determine the thickness distribution and variation of coal in the study area and to estimate and classify coal resources and determine the optimal distance from the borehole spacing. Estimation using kriging block results in the value of kriging relative error. Coal resource estimates and variability are determined based on kriging estimation with the relative kriging standard deviation (RKSD) method and the polygon method for classification based on sill distances. The number of drill holes used was 57 drill holes. Based on the calculation of the sill variogram, the coal measured resource is 150 meters, the coal indicated resource is 250 meters and the coal inferred resource is 500 meters. Based on the estimation and classification with relative kriging standard deviation (RKSD), the total coal measured resource is 1.8 million tons, the coal indicated resource is 3.2 million tons and the coal inferred resource is 2.5 million tons with total coal resources.

On-land alluvial tin mining activities produce residual materials from mineral processing or mineral washing; the major one of these is quartz sand, which can be utilized in the manufacturing industry. As time goes by, the reserves of alluvial tin are decreasing, which is in line with the increasing residual material from abundant mineral processing. Mining procedures are carried out following the Indonesian government regulations, covering mining as well as reprocessing. This motivated us to evaluate the potential of quartz sand at two mining sites in Bangka and Belitung Islands. This study evaluated alluvial tin processing residual quartz sand through drill hole spacing analysis (DHSA) by comparing two geostatistics parameters, namely global estimation variance (GEV) and kriging variance (KV). Drill hole samples were taken with varying spacing, ranging from 50 to 200 m, after which geostatistical analysis was carried out. With several simulations, the incorporation of GEV and KV was able to produce the optimal drill hole spacing with measured resource categories in the range of 40 to 55 m, indicated resources in the range of 55 to 85 m, and inferred resources >85 m. Accordingly, the total estimated quartz sand resources of both sites were obtained.

The analysis software, FLAC3D, was used for simulation of Nong'an oil shale mining according to the three-dimensional fast Lagrangian algorithm. A simulation study involving drilling hydraulic mining methods for different borehole spacings in the Nong'an oil shale mining area was conducted. The best mining scheme was selected in terms of safety factors and economic benefits, and used for the analysis of the vertical displacement and ground surface settlement of the oil shale area. Drill hole spacing was identified as a key factor for the coefficient of borehole hydraulic mining based on the general relationship between the coefficient and borehole spacing. The optimal mining hole spacing was 25 m, and the distribution regularities of the vertical displacement of the surrounding rock near the excavation and earth surface were observed. The results showed that FLAC3D can simulate and analyze the oil shale hydraulic mining process and is an effective and suitable method for oil shale exploitation research.

Hanging roofs can occur on a very large scale (generally can reach 15,000 m2) during the initial mining stages in longwall coal mining operations and are often a result of hard roof at the active mining face. Besides, when it suddenly fractures and caves, some risks and disasters would occur such as shock loading, wind blasts, and sudden gas extrusion from gob to working face. To control the size and competency of the hanging roof, Φ32-mm fracturing drills can create holes in the roof near the front and back coal walls, and Φ32-mm linear fracturing drills can be used to create holes in the roof at the face ends. The length of these drill holes is 3 to 5 times the height of the mining face and is based upon the principle that the gob should be fully filled with a caved roof to support vertical stresses, as well as the assumption that the broken-expansion coefficient of the rock is given as an empirical value. Considering the fracture propagation range and the support form of the cut, the drill-hole spacing is set to be between 1 and 2 times the single-hole crack propagation range. Hydraulic fracturing can generate main fractures and wing-shaped branching cracks inside the roof rock and can transform and weaken the roof structure, forming weak fracture plane favorable to roof caving. These fractures cause the roof to cave in a timely and adequate manner under in situ ground pressures. Successful field test in the no. 2 mine of Cuncaota, Shendong group indicated that the propagation range of hydraulic fractures is approximately 4–8 m. When the active face advanced 22.5 m, the roof beyond the hydraulic supports caves entirely, and gradually, the gob is fully filled with the caved roof and is absent of large voids. Thus, hazards such as shock loading, wind blasts, and sudden gas extrusion can be reduced or eliminated.

The prediction of the economic, geological, processing and technological factors affecting the definition of reserves — mining conditions, ore grade, market prices, mining costs and demand and supply of the minerals — are all associated with uncertainty. Some of these parameters are also dynamic and vary with time. Therefore, any reserve estimate must be a risk qualified statement commensurate with the conditions prevailing at the time of estimation. In the minerals industry, the economic and geological analyses of exploration data are conducted separately, i.e. the portion of the resource which is economically mineable is determined first followed by a division into measured, indicated and inferred resource categories depending on the degree of geological assurance about the deposit. This method of characterization uses direct and indirect geological evidence via the drillhole spacing and the estimates are not quatified with any degree of confidence or risk with respect to uncertainties arising from other factors such as market price. The developments in computer technology and the advances in interpolation and extrapolation techniques have resulted in tools which can quantify the level of confidence to be attached to the various estimates, However, serious questions remain on how well the assumptions of these techniques represent the ore mineralization phenomena and how much of geological information they incorporate. For example, is the variance of the estimates just a mathematical artifact or does it really have geological underpinnings? In this paper the concepts of uncertainty and risk as they relate to ore reserve and resource estimation and discussed and the role of mathematical and computer models in quantifying them is critically examined.

The assessment of drilling efficiency is strongly related to the rate of penetration (ROP) which is a vital parameter in evaluating the success of a drilling operation. Traditionally, the oil industry relies on the driller’s experience in selecting optimum operating parameters while drilling wells. An autonomous rotary drilling system with optimized ROP is the solution to mitigate drilling risks and reduce overall drilling costs. Developing a robust ROP model is a crucial step in optimizing its value and ultimately enhancing drilling efficiency. This study aimed to develop a predictive ROP model that uses direct and derived drilling parameters leveraging various machine learning algorithms, thereby providing a tool for drilling engineers to anticipate drilling performance and make data-driven operational decisions. A dataset of 6,279 measured ROP data points was gathered from five wells in the Volve Field, along with corresponding drilling parameters and real-time measurements. These parameters include weight on bit (WOB), rotary pipe speed (RPM), surface torque, pump pressure, mud flow rate, and equivalent circulating density (ECD). Additionally, derived controllable and uncontrollable variables, such as unconfined compressive strength (UCS), drilling mechanical specific energy (DMSE), and feed thrust force (FET), were computed using well-established correlations. First, data analytics and exploratory visualization are conducted to clean up the dataset and discover the relationship between ROP and feature inputs. Besides, a feature variable-importance analysis is implemented to identify the most crucial parameters affecting the ROP. For model development, five supervised regression machine learning algorithms were utilized. Additionally, in this study, the ROP model is developed as a function of drilling mechanical specific energy (DMSE), and feed thrust (FET). A comparative study of ROP predictions from the two approaches (surface operating and energy parameters) is presented. The findings of this study indicate that the Extra Trees (ET) model outperforms the other tested models in predicting ROP, with CatBoost (CB) and Random Forest (RF) following in accuracy. The ET model achieves an R² of 99% on the training set and 88% on the test dataset, demonstrating its superior predictive capability. The relative feature importance analysis reveals that surface torque and uniaxial compressive strength (UCS) have the greatest impact on ROP, while mud flow rate has the least influence. Furthermore, the model comparison study confirms that the proposed approach offers greater generalization compared to conventional models. The performance assessment highlights that ROP predictions based on derived parameters, such as DMSE and FET, are more accurate than those using surface operational parameters. This study presents a robust predictive model for accurately predicting the rate of penetration (ROP) using derived controllable drilling variables. The developed model addresses the limitations of conventional approaches and mitigates the uncertainties associated with empirical correlations. The findings offer valuable insights for the oil and gas industry, as precise ROP predictions contribute to improved drilling efficiency, particularly in complex operations, while also reducing overall drilling costs.

Drill-hole spacing analysis (DHSA) and optimization are becoming commonplace for uncertainty assessment and management in the mining industry. However, there is no standardized DHSA workflow, and the outputs of certain methodologies are not interchangeable. We group available simulation-based DHSA methods according to their accounted uncertainty into (i) raw uncertainty, assessed by drawing realizations from synthetic data-sets with the drilling spacings to be tested; and (ii) model uncertainty, in which these synthetic data-sets are used to assess the variation between the estimated model and the (unknown) actual value. DHSA workflows available in the literature ignore the differences between both types of uncertainty. Commonly, the DHSA algorithm is chosen without a detailed analysis of its uncertainty output, which may lead to misleading results and suboptimal decisions. While available solutions are based only on assessing raw or model uncertainty, the proposed approach simultaneously analyses both and their relationship for models at different stages of the mine. The integrated analysis results deliver more information to support decision-making than available methods. Principles, practical considerations, and discussions of the advantages of the proposed integrated analysis are presented. The approach is applied to a real gold deposit to illustrate its use.

Generally, the determination of resource classification is only qualitative based on the geometric factors and geological complexity that control it. However, as the prospect area is found to have a reasonably heterogeneous sediment characteristic, a method is needed that can be used to increase the level of confidence in determining the Optimum Drill Hole Spacing. Therefore, this study uses the application of geostatistics with the global estimation variance (GEV) method based on the relative error value of each parameter, namely the thickness geometry and quality in the form of Ash and VM. This research was carried out in Jangga Aur village, Bathin XXIV District, Batang Hari Regency, Jambi Province, Working Area of PT Berkat Bara Persada Jobsite PT Inti Bara Nusalima.The Drill Hole Spacing Analysis (DHSA) results will obtain optimum spacing on resource classification based on relative error values, namely 0-10% for measured resources, 10-20% for indicated resources, and 20% for Inferred resources carried out the on-seam reference. Based on the results of the study, it was found that the seam reference used was Seam D, then the spacing distance of the drill hole on the coal seam of the research area, which had an average distance of 80 m, with geostatic analysis could be increased up to a distance of 250 m in measured resources, indicated resources of 450 m and Inferred 800 m.

The primary objective of an E & P company is to drill and produce hydrocarbon at minimum cost with high level of safety without compromising environmental standards. With the current global downward slide in oil prices most E & P firms are slashing costs to shore up profitability. Drilling operations are high capital-intensive projects that drive unit production cost northwards. This paper presents a comparative analysis of drilling costs in three geographical locations of the world petroleum provinces viz; North Sea, Gulf of Mexico and Niger Delta with sensitivities of the various elements that affect drilling cost with a view to assisting operators and rig owners on optimizing activities in a lean environment. Relying on panel data sourced from databases of a global energy consultant and industry operators, historical absolute average cost and footage trends were compared during the period of 10 years (2005-2014). A randomly selected well cost data was used to carry out the sensitivity analysis to deduce key determinants. It was found that although there are regional differences that reflect the local geology and some economic factors, drilling times and all costs rise sharply with increasing depth. Also drilling cost for the Niger delta province is highest compared to the other two regions. The sensitivity study showed that the highest contributor to high drilling cost is the intangible element in which the rig rate, hole problems and security issues should be the focus in drilling cost reduction and economics. Contract renegotiation strategy to drive down rig rates and establish new market equilibrium is recommended in this lean environment. Also tangible costs from tubulars can be reduced with favourable policy on reviving Nigerian steel industries to enable local sourcing of these tubulars, improve employment rate hence reduce insecurity in the Niger Delta area.

Well spacing has a significant effect on gas reservoir deliverability optimization. A single well seldom provides the desired rate of production from a given reservoir. Generally, the total rate of gas production increases with the number of the wells completed in the gas reservoir. At the same time, inter-well interference tends to reduce this increase in total rate of production as the number of producing wells are increased. Consequently, there must exist a well-spacing which will result in the most efficient recovery from a natural gas reservoir. This optimum well spacing depends upon the producing formation characteristics as well as economics of field development. The overall objective of this paper is to provide a general guideline based on reservoir engineering principals for efficient well spacing pertaining to gas producing formations in West Virginia. The objective was achieved by developing a general reservoir model which simulates the flow of gas in a reservoir containing several wells. The model was then used to study the parameters which affect well interference and spacing. The model has the advantage of also accounting for the inertial component of pressure drop in gas flow through porous media, a factor which was found to affect well interference. Reservoir data pertaining to Big Injun and Benson formations were collected and interpreted. The interpreted data were statistically analyzed and the results were utilized in conjunction with the model to provide general guidelines pertaining to spacing for gas wells producing from these two horizons in West Virginia.

در معادن روباز استخراج ماده‌‌معدنی با حداقل قیمت و کیفیت مطلوب مهم‌ترین هدف معدن‌کاری است. در این مقاله تاثیر آب زیرزمینی بر روی هزینه‌های تولید و فرآیند معدن‌کاری مورد بررسی قرار گرفته است. به این منظور پارامتر سنگ‌شکنی ویژه (S_cr)، معرفی، اندازه‌گیری و مورد استفاده قرار گرفت. برای ارزیابی عملیات معدن‌کاری در شرایط خشک و مرطوب پایگاه داده در دو بخش هزینه‌های تولید و عملیات معدن‌کاری دو انفجار، چال‌های با قطر 6 اینچ ایجاد شد. اختلاف دو شرایط متفاوت معدن‌کاری در افزایش هزینه‌های تولید و کاهش عملکرد تولید مشاهده می‌شود. به طوری که هزینه‌های شامل هزینه حفاری، هزینه انفجار، مجموع هزینه حفاری و انفجار، هزینه بارگیری به ترتیب برابر با 33/83، 450، 67/266 و 200 درصد در شرایط معدن‌کاری مرطوب نسبت به شرایط خشک افزایش داشته است. هزینه سنگ‌شکنی به خاطر مقدار خردشدگی تقریبا مشابه در دو شرایط، یکسان بوده است. همچنین شرایط معدن‌کاری مرطوب باعث کاهش عملکرد تولید معدن مس سرچشمه را در پی داشته است به طوری که عملکرد تولید در بخش‌های شامل بارگیری ویژه و شاخص عملیات واحد معدن‌کاری ویژه به ترتیب برابر با 34/33 و 85/198 درصد نسبت به شرایط خشک کاهش داشته است. به منظور عدم استفاده از مواد منفجره ضد آب، بهبود شاخص عملیات معدن‌کاری و کاهش هزینه‌های تولید پروژه تعیین مدل آب زیرزمینی معدن مس سرچشمه امر ضروری است. با زهکشی آب زیرزمینی در معادن روباز، عملیات معدن‌کاری مطلوب با هزینه کمتر همراه با توسعه پایدار فراهم خواهد شد.

Efficiency of single-well geothermal systems with multi-lateral drills