مجله ژئومکانیک نفت
سال چهارم شماره 4 (زمستان 1400)

Underground storage of natural gas is mainly accomplished by three methods storage in depleted oil and gas reservoirs, storage in aquifers, and storage in salt domes. Among these methods, underground storage (UGS) in aquifers is of much paramount due to more accessibility to metropolises and consumption markets, proper conditions, and ability to keep the gas for long period of time. So far, storage of natural gas in aquifers has been studied from various aspects, but from a geomechanical point of view, no studies have been conducted to date. So, in this study, in order to investigate the geomechanical parameters affecting the process of underground storage of natural gas in an aquifer, the process has been simulated by Finite Element Method (FEM) using ABAQUS software and the geomechanical parameters affecting this process have been studied. For this purpose, first, the impacts of gas injection and production on pore pressure and vertical displacement in different times and locations are thoroughly investigated after injection and production phases. Afterwards, the sensitivity analysis is done regarding to the input parameters of the model. The results showed that the ratio of horizontal stresses to initial vertical stress is considered to have the maximum impact on increasing the probability of tensile failure. Also, injection/production rate and the horizontal stresses to initial vertical stress ratio have the greatest influences on probability of shear failure respectively. Besides, injection/production rate and reservoir Young modulus have the highest impact on vertical displacement respectively. The highest vertical displacement after injection phase and after production phase are 8 at the injection location and 12 (mm) at the production location, respectively. In addition, the highest increase of pore pressure took place around injection wells one-year after injection start time which is equal to 534 KPa compared to the aquifer initial pressure.

Machine Learning algorithms have widely been adopted to group well log measurements into distinguished lithological groupings, known as Facies/Geomechanical units. This procedure can be achieved using either unsupervised learning or supervised learning algorithms. Supervised learning is the most common and practical of machine learning tasks and it is designed to learn from the example using input data that has been mapped to the correct output. In this research, we can run the modeling using Unsupervised Learning, where we authorize the algorithms to recognize underlying patterns within the data that may not be easily visible during data exploration. Therefore, an unsupervised learning method has been used to determine geomechanical zones. In this method, we give one's consent/assent to algorithms to identify subsurface patterns using data that may not be easily visible during data exploration. First, the application of practical methods of machine learning algorithms, including the K-mean model, Based Spatial Clustering of Applications with Noise (DBSCAN), Hierarchical Agglomerative Clustering (HAC), and Gaussian mixed model, will be explained, And then in this research, the best method for predicting petrophysical layers will be presented and compared the results with an established Lithofacies curve. The required programming is done in a Python environment. In this regard, after well processing, The XGBoost and Multi-Layer Perceptron Neural Network Algorithms have been used to predict the missing data. The optimal number of clusters is obtained using an ‘elbow’, In this article, as the title suggests, Four methods are used in cluster analysis unsupervised machine learning algorithms, but in petrophysical, geological, and geomechanical realities, data seldom conform to good circle patterns. Whereas if the data clusters are circular, K-Means clustering and Hierarchical Agglomerative Clustering( HAC) work great. Therefore, it is better to use the Gaussian mixed models (GMM) method.

With the increasing need for energy and the dependence of various industries on fossil fuels, oil and gas experts have been forced to think about increasing production from existing fields. These conditions necessitated the introduction of new methods for this purpose for oil and gas reservoirs, the most important of which was the use of hydraulic fracturing methods. Numerous factors can affect the condition of the fracture and its geometry, which can be noted as the existence of natural fractures as one of the most important factors. The geometric properties of natural fractures can affect how the operation is performed and the type of hydraulic fracture created; Therefore, studying them before performing the operation is inevitable. In this study, natural fractures have been investigated using a discrete fracture network and the hydraulic fracturing process using a numerical method based on discrete element method. In this regard, the geometric properties of fractures such as density, fracture length and orientation and its effect on hydraulic fractures have been studied. The results indicate that the characteristics of the discrete fracture network and the geometry of the fractures can influence the hydraulic fracturing operation and control the results, and in most cases provide promising results in estimating the reservoir response to fluid injection.

After drilling wells for obtaining oil from drilled formation based on the availableinformation which was received from the illustrators, the points where theprobability of oil content is more than other points are identified. Now, the walls ofdrilled wells perforated in some net points where the possibilities of having oil inthis condition are more than the other state of affairs. Perforation of the productionlayer will be a very crucial and effective process in the operation of wellborecompletion. In fact, it can be said that perforation is the main key to achieving oil inhydrocarbon reservoirs after drilling wells. In this thesis, based on preliminary datarelated to one of the formations of southwestern Iran, 3D modeling has been doneby Flac3D software in order to determine the optimal perforation direction toachieve more production. Flac3D is a static-dynamic program which performs fastLagrangian Analysis by finite difference method. To model the proposition, thestrain softening behavioral model has been used in Flac3D software.This model has been designed as a constant discharge. In order to optimizeproduction from the well, factors such as displacements of perforations, strain shearplastic and stress concentration in critical points have been investigated by applyingdifferent scenarios of oriented perforations.The results show that the optimal angle is obtained when the perforations are one inthe direction of minimum horizontal stress and the other in the direction ofmaximum horizontal stress which makes a 90degree angle together.

Hydraulic fracturing process is one of the most important technologies that can be used to increase the exploitation and production from low permeability oil and gas fields.Due to the high cost of hydraulic failure, the necessary and sufficient studies on the properties of rock and fluid and the field of stresses in the depths of the earth should be done before performing the operation.For this purpose, in this study, using artificial samples in the laboratory, the effect of porosity on fracture pressure, type of crack and also the effect of different lateral pressures on fracture operation were investigated.The studies showed that with increasing lateral pressure, the fracture pressure increases and at high lateral pressure and the crack deviates from the vertical position. Also, with increasing porosity for samples R10, R30, R20 and R40 by %15, %19, %20 and %13, respectively, the hydraulic failure pressure at 2 MPa compressive pressure decreases by %20, %22, %37 and 19% At 3 Mpa decreases by %25, %33, %20 and 12%, and at 5 MPa decreases by %20, %25, %35 and %20. At higher lateral pressures, this effect is less.

Proper determination of the safe mud weight window is important in order to reduce the risk of mud loss and also reduce the risk of well eruption and ultimately will create safe drilling and increase the speed of drilling operations. In this research, one of the wells of the Maroon oil field in southwestern Iran has been investigated as a case study. To estimate the geomechanical parameters, including the mechanical parameters of the rock, the pore pressure, as well as the stresses of the region, sound well loges and proper experimental relationships have been used for the field. After estimating the geomechanical parameters and constructing the geomechanical model, the constructed model is validated to ensure accuracy. After preparing a valid geomechanical model, the stability of the well is analyzed using the two criteria of Mohr-Columbus and Mogi-Columbus failure, and the application of the above criteria in determine " mud weight safe window" is compared. The results show that the Moggi-Columbus criterion better than the Mohr-Columbus criterion recognizes the fractures created in the studied well, such as the Breakout event. To validate the geomechanical model and confirm the efficiency of the empirical criteria used in detecting the breakout event, numerical simulation of wells in two steps of geostatic and drilling was performed. The simulation results indicate the formation of a breakout event in the depth of the study and thus confirm the method used in this paper.