H. Yousefian; M. Fatehi Marji; H. Soltanian; A. Abdollahipour; Y. Pourmazaheri
Abstract
Determination of the borehole and fracture initiation positions is the main aim of a borehole stability analysis. A wellbore trajectory optimization with the help of the mud pressure may be unreasonable since the mud pressure can only reflect the degree of difficulty for the initial damage to occur at ...
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Determination of the borehole and fracture initiation positions is the main aim of a borehole stability analysis. A wellbore trajectory optimization with the help of the mud pressure may be unreasonable since the mud pressure can only reflect the degree of difficulty for the initial damage to occur at the wellbore rather than the extent of the wellbore damage. In this work, we investigate the failure extension in different arbitrary inclination boreholes under different in-situ stress regimes. Assuming the plane strain condition, the Mohr-Coulomb, Mogi-Coulomb, and Modified Lade rock failure criteria are utilized. We present an analytical equation to determine the optimum drilling trajectory of an Iranian oilfield. In order to predict the degree of wellbore damage, the initial shear failure location, failure width, and failure depth of arbitrary wellbores are determined. Then a new model is derived to calculate the initial failure area of a directional wellbore because it is more efficient in a wellbore stability analysis. The results obtained show that in the target oilfield, the vertical and low-deviated direction is the optimum drilling path. According to the results of this work, optimization of the wellbore trajectory based on the estimated failure zone is a reasonable method if a considerable failure zone takes place around the borehole wall.
M. R. Azad; A. Kamkar Rouhani; B. Tokhmechi; M. Arashi
Abstract
Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will ...
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Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will be merged, and vice versa, they will remain fine with severe variability. Bandwidth variation can be effective in upscaling results. Therefore, determining the optimal bandwidth in this method is essential. For each bandwidth, the upscaled model has a number of upscaled blocks and an upscaling error. Obviously, higher thresholds or bandwidths cause a lower number of upscaled blocks and a higher sum of squares error (SSE). On the other hand, using the smallest bandwidth, the upscaled model will remain in a fine scale, and there will be practically no upscaling. In this work, different approaches are used to determine the optimal bandwidth or threshold for upscaling. Investigation of SSE changes, the intersection of two charts, namely SSE and the number of upscaled block charts, and the changes of SSE values versus bandwidths, are among these approaches. In this particular case, if the goal of upscaling is to minimize the upscaling error, the intersection method will obtain a better result. Conversely, if the purpose of upscaling is computational cost reduction, the SSE variation approach will be more appropriate for the threshold setting.
M. Dehvedar; P. Moarefvand; A.R. Kiyani; A. R. Mansouri
Abstract
Inadequate hole cleaning can lead to many problems in horizontal and directional wells. In this work, we tried to investigate the cutting transport phenomenon by an experimental directional drilling simulator, considering the differences between the operational and experimental conditions. The inclination, ...
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Inadequate hole cleaning can lead to many problems in horizontal and directional wells. In this work, we tried to investigate the cutting transport phenomenon by an experimental directional drilling simulator, considering the differences between the operational and experimental conditions. The inclination, fluid type (water, foam, viscous, and dense), rotary speed (0 and 110 rpm), nozzle bit size (4, 6, and 8 mm), and stabilizer location (8 and 95 cm from the bit) were included in the tests as the main parameters. It could be concluded that the nozzle size and the stabilizer position influenced the hole cleaning time. In vertical wells, by decreasing the nozzle size from 8 mm to 4 mm, the hole cleaning time was increased. The presence of stabilizer reduced the cleaning time, and optimizing the stabilizer position reduced the probability of cutting bed formation in all inclinations. Finally, a third polynomial equation was fitted between the dimensionless mass and the dimensionless cleaning time.
B. Tokhmechi; M. Rabiei; H. Azizi; V. Rasouli
Abstract
A complete and accurate analysis of the complex spatial structure of heterogeneous hydrocarbon reservoirs requires detailed geological models, i.e. fine resolution models. Due to the high computational cost of simulating such models, single resolution up-scaling techniques are commonly used to reduce ...
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A complete and accurate analysis of the complex spatial structure of heterogeneous hydrocarbon reservoirs requires detailed geological models, i.e. fine resolution models. Due to the high computational cost of simulating such models, single resolution up-scaling techniques are commonly used to reduce the volume of the simulated models at the expense of losing the precision. Several multi-scale techniques have also been developed for simulating heterogeneous reservoirs including those in which a limited number of blocks down-scale, i.e. splitting coarse blocks into fine cells around the well-zones in the case of simulation of hydraulic fracturing. In these cases, locally computed basis functions are employed to construct a global solver at a coarse-scale such as wavelet- and kernel-based up-scaling techniques. In this paper, a novel/robust 2D block-ordering system is presented, which enables solving multi-resolution up-scaling fluid flow simulations. The results will be described for a simple model, and fluid flow equations will be developed in order to show the structure of transmissibility matrix. It is confirmed that with a developed block-ordering system not only the accuracy of history match increases but also the CPU time decreases.
J. Ghiasi-Freez; M. Ziaii; A. Moradzadeh
Abstract
An accurate reservoir characterization is a crucial task for the development of quantitative geological models and reservoir simulation. In the present research work, a novel view is presented on the reservoir characterization using the advantages of thin section image analysis and intelligent classification ...
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An accurate reservoir characterization is a crucial task for the development of quantitative geological models and reservoir simulation. In the present research work, a novel view is presented on the reservoir characterization using the advantages of thin section image analysis and intelligent classification algorithms. The proposed methodology comprises three main steps. First, four classes of reservoir intervals are defined using a limited number of porosity and permeability values obtained from the core plugs of Kangan and Dalan formations. Then seven micro-scale features including distribution of pore types (interparticle, interaparticle, moldic, and vuggy), pore complexity, and cement distribution as well as textural characteristics are extracted from thin section images. Finally, the features extracted from each photomicrograph and its corresponding reservoir class are used as the training data for several intelligent classifiers including decision trees, discriminant analysis functions, support vector machines, K-nearest neighbor models and two ensemble algorithms, named bagging and boosting. The relationship between the micro-scale features and the reservoir classes was studied. Performance of all classifiers is evaluated using the concepts of accuracy, precision, recall, and harmonic average. The results obtained showed that the bagging decision tree delivered the best performance among the models and improved the accuracy of simple models up to 7.7% compared with the best single classifier.
A. Abdollahipour; M. Fatehi Marji; H. Soltanian; E. A. Kazemzadeh
Abstract
The permeability and coupled behavior of pore pressure and deformations play an important role in hydraulic fracturing (HF) modeling. In this work, a poroelastic displacement discontinuity method is used to study the permeability effect on the HF development in various formation permeabilities. The numerical ...
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The permeability and coupled behavior of pore pressure and deformations play an important role in hydraulic fracturing (HF) modeling. In this work, a poroelastic displacement discontinuity method is used to study the permeability effect on the HF development in various formation permeabilities. The numerical method is verified by the existing analytical and experimental data. Then the propagation of a hydraulic fracture in a formation with a range of permeabilities is studied. The time required for propagation of an HF to 10 times its initial length is used to compare the propagation velocity in the formations with different permeabilities. The results obtained show that the HF propagation can be significantly delayed by a permeability less than almost 10-9 D. Also the effect of HF spacing on the propagation path is studied. It was shown that the stress shadowing effect of HFs remained for a longer spacing than in the elastic model due to the required time for fluid leak-off in the formation. Also the propagation angles are higher in the poroelastic model predictions than the elastic model. Therefore, it is proposed to use the poroelastic model when studying multi-HF propagation in order to avoid errors caused by neglecting the pore fluid effects on the HF propagation paths.
M. Abedini; M. Ziaii; Y. Negahdarzadeh; J. Ghiasi-Freez
Abstract
The porosity within a reservoir rock is a basic parameter for the reservoir characterization. The present paper introduces two intelligent models for identification of the porosity types using image analysis. For this aim, firstly, thirteen geometrical parameters of pores of each image were extracted ...
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The porosity within a reservoir rock is a basic parameter for the reservoir characterization. The present paper introduces two intelligent models for identification of the porosity types using image analysis. For this aim, firstly, thirteen geometrical parameters of pores of each image were extracted using the image analysis techniques. The extracted features and their corresponding pore types of 682 pores were used for training two intelligent models, BPN (back-propagation network) and SAE (stacked autoencoder). The trained models take the geometrical properties of pores to classify the type of six porosity types including intra-particle, inter-particle, vuggy, moldic, biomoldic, and fracture. The MSE values for the BPN and SAE models were found to be 0.0042 and 0.0038, respectively. The precision, recall, and accuracy of the intelligent models for classifying the types of pores were calculated. The BPN model was able to correctly recognize 193 intra-particle pores out of 197 ones, 45 inter-particle pores out of 50 ones, 7 vuggy pores out of 9 ones, 10 moldic pores out of 12 ones, 2 biomoldic pores out of 3 ones, and 6 fractures out of 7 ones. Also the SAE model was able to correctly classify 193 intra-particle pores out of 197 ones, 46 inter-particle pores out of 50 ones, 8 vuggy pores out of 9 ones, 10 moldic pores out of 12 ones, 3 biomoldic pores out of 3 ones, and 7 fractures out of 7 ones. The results obtained showed that the SAE model carried out a bit more accuracy for classification of the inter-particle, vuggy, biomoldic, and fracture pores.
