نشریه روش های تحلیلی و عددی مهندسی معدن
پیاپی 32 (پاییز 1401)

The Persian Gulf basin is one of the most important regions in terms of hydrocarbon resources in the world. The Kish gas field is located in the eastern part of the Persian Gulf.  The purpose of this paper is to assess the hydrocarbon generation potential and to model the burial and thermal history of source rocks in this gas field using Rock-Eval pyrolysis, vitrinite reflection, and a 1D model.

Methodology and Approaches:

In this study, 58 rock samples were selected from layers with high natural gamma ray in Pabdeh, Gurpi, Ilam, Lafan, Sarvak, Kazhdumi, Dariyan, Gadvan, Fahliyan, Surmeh, Neyriz, Dashtak, Dalan and Faraghan Formations for Rock Eval pyrolysis and vitrinite reflection. In addition, one-dimensional modeling of burial and thermal history was performed using PetroMod software (2011-Schlumberger) on well B of the Kish field.

The TOC and S1+S2 values vary from 0.16 to 1.59%, and from 0.08 to 4.16 mg HC/g Rock, respectively. Most of the samples have low hydrocarbon potential, only a limited number from Gurpi and Pabdeh show fair hydrocarbon generation potential. The samples with fair potential have kerogen type III and II/III with the low level of maturity. The one-dimensional modeling was performed on Pabdeh, Gurpi and Sarchahan source rocks. The thermal model was calibrated with corrected down-hole temperatures and vitrinite reflections. According to the model, Pabdeh and Gurpi are immature, while the Sarchahan is currently in the gas window. It has reached the oil and gas window since 160 and 120 million years ago, and produced 95% of its potential so far.

Evaluation of permeability and fluid flow behavior in rock joints is one of the most critical and fundamental issues in many rock engineering projects. In recent years, changes in the permeability of rock joints and mechanical deformations of the rock mass with the effects of chemical reaction have been studied by H-M-C process. Shear-flow coupling tests are generally performed under conditions where the flow direction is either parallel to the cutting direction or radially from the center of the joint sample due to the limitations of difficult laboratory conditions. One of these difficulties is the complete insulation of the sample to create a one-dimensional linear flow in the direction of the shearing. Numerical simulations can eliminate laboratory difficulties with flow sealing conditions. In this paper, the influence of chemical agents on fluid flow while the shearing process is applied. Due to the difficulties of implementing this issue, modeling has been done by developing a computational code using the finite element method.

Designing a coupling process with simultaneous effect of hydro-mechanical-chemical phenomena, numerical modeling based on the finite element method has been used to study the effect of shear displacement on fluid flow rate when fracture surfaces are degraded. The hydraulic head pressure (equal to one meter of water) is applied to the flow's input, and zero pressure is applied to the flow's outflow to simulate and quantify the flow rate from the fracture's left to right. The upper and lower boundaries of the fracture are also sealed. In the next step, because the fluid flow is to be examined separately in the X and Y directions, then, in each step, the flow in the conduct of outlets must be opened in the desired direction and closed in the other directions. To apply the effect of shear displacement on the flow rate, a secondary code based on the changes in the elements due to shear displacement was used and added it to the computational process of the developed primary code. The aperture values in each step are calculated and returned to the original code to calculate the flow rate step by step.

The results show that with increasing the shearing rate in both conditions before and after acidizing, the flow rate has an increasing trend. Also, the fluid flow pattern goes channelized with an increasing shear rate. After acidizing the joint surface, the difference between the roughness coefficient and the linear roughness of the two fracture surfaces increases, which increases the initial hydraulic conductivity of the fracture, and flow changes shows a lower trend compared with the conditions in the pre-acid state. In some cases, the trend of discharge rates in the conditions after acidizing does not follow the general pattern of discharge rates. It seems it’s caused by closures which are created by shear displacement in the fluid flow path, forcing the fluid to change direction and find a new path to pass through the joint.

The purpose of grouting is to strengthen and improve the mechanical and hydraulic properties of the rock and soil. The fluid that is injected into the cavities and fissures of the environment is like a viscous liquid consisting of grains whose size is important in the grouting operation. Therefore, determining the groutability ratio in grouting operation is considered as an important parameter. Today, studies using data mining science show that the groutability of granular soils, in addition to grain size, is affected by various factors of the soil and the material of grout, which predicts groutability more accurately. Throughout history, many researchers have predicted groutability through experimental relationships. However, today, the capability of data mining methods in accurate predictions has shown that one approach in predicting groutability is to use a variety of data mining models and inferential systems.

Methodology and Approaches:

The purpose of this study is to evaluate several models of data mining methods, including ANN, SVM, KNN, RF and NB. For this purpose, a set of laboratory information related to groutability has been used in four literatures that include 87 data in order to develop efficient models for predicting groutability. Classification models are created in Orange software.

The output variable is a property of groutability, which as a binary variable has two states of zero meaning nongroutable and 1 meaning groutable. Input variables also include the ratio of water cement in the grout or viscosity (W/C), the relative density of the soil (Dr), grouting pressure (P), the percentage of the soil particles passing through a 0.6 mm sieve (FC), N1 = D15soil / D85 grout and N2 = D10 soil / D95 grout. The values of the evaluation criteria for the methods are almost close to each other. Based on the AUC index, the random forest is the best model and the k-nearest neighbor method has the lowest value of this index. However, in terms of other criteria, the artificial neural network is higher than other methods and the k-nearest neighbor method is very close to it. On the other hand, the random forest model has the lowest value of criteria. Ignoring the AUC criteria, ANN and KNN methods are the best methods.One of the capabilities of Orange software is to study the effect and importance of input variables on the prediction of the target variable, in other words, the sensitivity of the output variable to input variables. The results show that variable N2 is in the first level based on the three criteria of information gain, relative information gain and Gini index, and variable N1 is in the second level with a very small difference in the values of the criteria. In addition, in the last row, W/C has the lowest value of the criteria and shows a small role in the correct prediction of groutability.

Discontinuities are the most important factor in the disorder and the impossibility of achieving ideal conditions. Sometimes in geomechanical study areas, joint studies are performed before tectonic studies. The reason is the lack of necessary outcrops to identify thetectonics of the area or uncertainties in their location. Therefore, the problem is to find a solution to estimate the position of large-scale structures, especially faults. From this perspective, in previous research, several points have been proposed to identify such structures:Joint density usually increases in areas near the faults. The distribution of discontinuity dip and dip direction, near the faults is generally severe. Alteration and weathering are high in the areas around the faults.

Methodology and Approaches:

In this study, increasing the distribution of discontinuity dip and dip direction and its relationship with the location of large tectonic structures has been used as a hypothesis. The Fisher coefficient (K) represents the scatter of the Fisher variable distribution function. Logically, in tectonized regions and fault zones (fault crossing areas), the distribution of the dip and dip direction of the joints is higher. As a result, the Fisher constant (K) decreases at the fault crossing point and increases at the inter fault zone. Based on this feature, areas with more tectonic mobility can be separated from structural calm areas and the Fisher's constant coefficient is introduced as a parameter determining the order of discontinuities.

By taking primary data, including the dip and dip direction of the discontinuities from the four mines of Sechahoon, Ghoghart, Meiduk, and Esfordi phosphates, the distribution of K coefficient and drawing the contour lines based on the Fisher coefficient, the fault system in the study area was identified. Thus, areas with a high concentration of K coefficient in each mine were considered as fault crossings. By comparing the tectonic blocks enclosed between the faults of each mine and its relative compatibility with the separated areas by the proposed method, the efficiency of this method to identify the joint system and estimate the position of large tectonic structures was well achieved.

Over the last three decades, several methods have been proposed to assess the rockfall hazard in the highways and mines. In open-pit mines, rockfalls threaten not only human lives, but also machinery and portal structures located at the toe of highwalls. Therefore, rockfalls are one of the major hazards in open-pit mines. Qualitative or quantitative procedures can be used to distinguish between hazard classes.

Methodology and Approaches:

One of the basic methods for stability analysis of the dolomite wall, especially on rock slopes, is to assess the rockfall hazard. In this paper, a qualitative rockfall hazard assessment method, named qualitative Evolving Rockfall Hazard Assessment (ERHA) and RocFall software which is specifically developed for the assessment of rockfall hazards, is used. In this method, based on the visual monitoring system, unstable blocks are recognized and Rockfall hazard is evaluated. In the study, the dolomite wall Golbini 7 Mine was divided into 13 different zones and in each zone, blocks prone to instability were identified. The total number of the evaluated blocks is 46 cases. All blocks analyzed by qualitative rockfall hazard assessment method and RocFall software.

The blocks related to zone 8 have a medium to high risk level and all blocks related to zone 13 have a high hazard level. No block is at the low hazard level. Only 2% of the assessed block are in the low to medium hazard level. 9% are in the medium hazard level, 50% are in the medium to high hazard level and 39% are in the high hazard level. The rockfall distance from the toe of the face determined by the evolving rockfall hazard assessment method and the results are compared with the modeling results by RocFall software. The maximum difference between the results is 25%.

There are different methods to determine in situ stress. In this regard, direct measurement methods are the best and most accurate in situ stress measurement methods. However, these methods are very time-consuming and costly. Therefore, nowadays laboratory and indirect rock core-based methods for estimating in situ stress have been taken into consideration. One of the laboratory methods is the acoustic emission method based on Kaiser effect. In this method, determining the Kaiser effect point is usually done by the parameters of acoustic emission signals, which in some cases, determining the Kaiser effect point by parametric method are ambiguous and do not have sufficient clarity. Signal processing based on wavelet transform is a powerful tool to process acoustic emission signals, which has been used in several papers.

Methodology and Approaches:

In this study some Phyllite samples were used to be loaded under indirect tensile loading (Brazilian test). The acoustic emission test consisted of two cycles. In the first cycle, the samples were preloaded to a predetermined level, and in the second cycle, they were reloaded until reaching the failure. Before using the discrete wavelet transform, the appropriate mother wavelet was selected. Then, the signals obtained from the acoustic emission test were processed using wavelet transform. The maximum approximation coefficient parameter was used as a suitable feature for the analysis. Using K-means method, the obtained data are clustered in five clusters. Then, the highest density of data in the fifth cluster was considered as the occurrence point of the Kaiser effect.

The results show that according to the parameters of correlation coefficient and noise to signal ratio and the type of acoustic signals the mother wave db6 was suitable for analysis. Among the parameters that can be used for analysis, the maximum approximation coefficient parameter is also selected as a suitable feature for analysis. Also, the results of the discrete wavelet transform method were in good agreement with the results of the parametric method, so that the occurrence times of the Kaiser effect obtained from the two methods are mutually acceptable.

The aim of the planning process for an open pit mine is usually to find optimum annual schedules that will give the highest Net Present Value (NPV). The primary input of this procedure is an economic block model, which includes a set of mining blocks representing the ore body and the surrounding rock. Net economic value is assigned to each block based on the revenue of recoverable metal content in a given block and subtracting all the operating costs, comprising mining, processing, refining, and selling costs. An economic evaluation of each block requires the estimation of ore tonnage and grade of mining blocks as well as some economic parameters such as metal prices and operation costs. In the current pit design approaches, the block economic values are calculated using a fixed known value. In this paper, using the metal prices in the past as well as the Monte Carlo simulation method, the most probable ultimate pit is obtained.

Methodology and Approaches:

In this article, the price distribution function of the metal price (copper) was obtained using the metal price history. Then 100 prices were simulated using Monte Carlo simulation and the expected value of each block was obtained using these simulated values of other fixed technical and economic parameters. Finally, by using these values and using the NPV Scheduler software, a single optimal pit was obtained. 

In this article, the expected value of the blocks was obtained using the Monte Carlo simulation method, and then the optimal pit, which is actually the most probable pit, was obtained. Because the price history of the metal is considered in the design process, the obtained pit has little sensitivity to the changes in the price of the metal in the future.