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The oil and gas industry is moving towards the use of nonmetallic pipeline material, such as reinforced thermoplastic and flexible piping, for applications in offshore fields. However, these materials have certain pressure and diameter constraints that require careful analysis prior to deciding on the appropriate piping material to be installed. The objective of this paper is to suggest an integrated approach that considers the reservoir properties, well path and the field pipeline network to determine the operating pressure and diameter that is ultimately used to select the appropriate pipeline material for offshore field developments. The proposed integrated model uses a series of three optimization techniques to determine the optimum field development architecture, which includes the allocation of wells, pipeline network configuration and well path optimization. The model starts by applying a continuous optimization technique to find the optimum subsurface and surface network. It then uses a graph-theorical approach to find the optimum pipeline route based on an appropriate minimum radius of curvature while considering the presence of obstacles in the seabed. From the results of this optimization, a dynamic nodal analysis is applied to determine the optimum operating conditions of the field (e.g.
Artificial Islands are often an effective strategy to develop shallow-water fields. However, their layout and design are affected by numerous drilling and surface facility constraints, such as water depth, number of wells, proximity to shore, and well spacing. When these constraints cannot be honored, conventional offshore wellhead platforms must be installed instead. This paper reviews previous artificial island projects to identify their key constraints, and then proposes a numerical model that accounts for these constraints when determining whether artificial islands or offshore platforms would generate the highest Net Present Value (NPV) configuration.
The model uses a combination of discrete and continuous mathematical algorithms to find the optimum development plan in shallow-water fields. Specifically, the model analyses the water depth, drilling and surface facilities of the field to suggest the optimum facility type to drill the wells using a k-means algorithm and Mixed-Integer Linear Programming (MILP). Then, a local optimization routine is used to connect islands to well targets. The model accounts for limitations on well spacing and the well paths to ensure that wells conform to the available drilling-rig capabilities and well-pad design requirements. The overall field configuration is optimized using a stochastic-perturbation method that adjusts the field network to maximize the NPV of the development.
The model explores the numerous possible scenarios that exist when planning shallow-water offshore field developments, especially when a high number of wells is required. The coupling of continuous and discrete optimization techniques provides a quick and effective method to analyze these possible scenarios and select an optimal strategy. Results from the model indicate that offshore wellhead platforms are not always favored over artificial islands in offshore field developments, particularly when extended reach wells are present. This is illustrated with a case study that demonstrates each stage in the integrated model starting from the analysis of the reservoir simulation model, through to well planning, and design of the facility network. The study highlights how such integrated analysis can aid in the selection of the highest development NPV plan in shallow-water fields by not only minimizing the cost associated with the development but also reducing the time required to generate the optimum plan.
A wide range of modified cable bolts are currently used for ground support in different conditions in Australian underground coal mining operations. This is mainly based on the belief that the performance of modified cable bolts is better than conventional cable bolts. Despite this positive view, very few studies have characterised the performance of modified cable bolts in service. A new laboratory based pull-out testing facility was employed in this study to investigate the behaviour of two different types of modified cable bolts under axial loading including Garford twin strand bulbed and MW9S (Spiral wire). The impact of different parameters including the compressive strength of the grout and the confining medium as well as borehole diameter on the performance of both cable bolt was investigated. A full factorial experimental program was designed based on Taguchi method to explore the performance of these two cable bolts under different testing conditions. Consequently, an Analysis of Variance (ANOVA) was conducted to assess the weighting contribution of each parameter (e.g. borehole diameter, the compressive strength of grout and confining medium) to the load-displacement performance of Garford twin strand bulbed and MW9S cable bolts. For the Garford twin strand bulbed cable bolt, it was concluded that the compressive strength of the confining medium was the most influential parameter in the determination of the peak and residual loads as well as initial stiffness. It was also observed that an increase in the compressive strength of either the confining medium or the grout led to an increase in peak and residual loads in the Garford twin strand bulbed cable bolt while borehole diameter had no sensible effect on peak and residual loads as well as initial stiffness. In the case of the MW9S cable bolt, the compressive strength of grout had the greatest impact on the peak and residual loads whereby, the peak and residual loads varied directly with grout compressive strength. A 10 mm increase in borehole diameter of MW9P cable bolt had negligible effect on the peak and residual loads as well as initial stiffness.
A porosity segmentation technique has been proposed in this work. Scanning Electron Microscopy (SEM) is often used as a non-destructive technique to obtain microscale images of rock samples. These images pose various difficulties before the user. Unlike sandstones, carbonates display a large heterogeneity in their pore-size distribution owing to their evolution. Additionally the quality of the image often mandates several image processing steps before they can be used for interpretation tasks. This variation appears due to irregular distribution of intensities in the pixel values of the SEM image. Conventional techniques of global binarization used in extracting the porous part suffer due to this reason. This work introduces a novel method of optimizing the various image processing parameters for proper extraction of porous part. The proposed method implements the Simulated-Annealing (SA) based global optimizer for finding optimum values of these parameters. Results of the application on five SEM images have been shown. The images are processed with optimum choice of parameters after preprocessing. Finally, we report the total porosity in terms of pore and throat porosity.
ABSTRACT: The dynamic shear fracture characteristics and mechanisms are studied, by utilizing a novel triaxial split Hopkinson pressure bar (3D-SHPB) and a modified configuration of punch-through shear samples. Two types of rocks with similar uniaxial compressive strength are chosen; one is granite which is an igneous rock that is polymineralic, the other is marble which is monomineralic and relatively homogeneous. The mineral content and grain structure of two rock types are identified using petrographic thin sections. The strain rate effect of rock shear strength under triaxial confining conditions has been studied by controlling the impact velocity of the striker. Both rock types exhibit strain rate effect with increasing shear strength; granite has higher shear strength and failure strain, while marble has lower shear strength and strain. The microscopic characteristics of dynamic shear fracture for different rocks are examined using scanning electron microscope. Different minerals undergo different failure modes during dynamic shear fracturing, as identified by SEM studies on the fracture surfaces.
The shear strength and failure characteristics of intact rock are crucial for research and design in rock mechanics. There are many experimental configurations that aim to achieve mode II fracture in testing samples, the punch-though-shear method was originally designed by Watkins (1983) to study the shear fracture toughness of soil-cement samples, and was later proved experimentally and numerically by Davies and So (1986) that this specimen design generates Mode II fracture mode in the material. Backers et al. (2002) and Backers (2004) studied the effects of sample geometry, materials, confining stress, as well as the micromechanics of rock damage under mode II fracturing conditions. In turns of research for earthquake and natural science, shear testing methods have also been utilized to investigate the shear failure characteristics by Ko and Kemeny (2011), which included the effect of loading rate, confining stress and water content on the subcritical shear fracture growth.
ABSTRACT: The poro-mechanical response of porous rocks is usually defined by Biot effective stress concept. Gas sorbing rocks such as coal do not however follow the conventional effective stress law because of swelling associated with gas adsorption and therefore, modification to the law is required. The Biot coefficient of non-reactive porous rocks is readily measured by jacketed-unjacketed experiment however, there is no standard definition neither any procedure to characterize the poro-mechanical response of gas sorbing rocks. This extends to jacketed-unjacketed measurements where it is not clear as to what these measurements represent in a gas sorbing rock such as coal sample and how the results should be interpreted.
In this study, therefore, the conventional jacketed-unjacketed tests were performed on coal samples using adsorptive (CO2) and non-adsorptive (Helium) gases. As expected the Biot coefficients measured by He and CO2 are significantly different. The results of the conventional jacketed-unjacketed experiments showed that the swelling as a volumetric strain is only partly responsible for variation of Biot coefficient when adsorptive gas is used and the Biot coefficient is pressure-stress dependent. The mechanical alteration (bulk modulus in particular) of the sample induced by this gas adsorption seems to be another mechanism influencing poro-mechanical response in a very complex way. In order to shed light on the macro-scale observations, 3D X-ray micro Computed Tomography technique (micro-CT) was used to investigate the internal structural changes of coal sample undergoing stress with a) no pore pressure, b) pressurised Helium and c) pressurised CO2. The micro-scale changes were then linked to macro-scale observations and their effects on measured Biot coefficients were discussed.
The effective stress concept was first introduced by Terzaghi (1923) for unconsolidated granular materials. However rocks have solid skeleton that makes their poromechanical response different from that of cohesionless sediments. Biot (1941) later employed this concept to develop the linear poroelastic theory for cohesive materials such as rocks where the effect of solid skeleton was taken into account. In the Biot theory, the effective stress, σ’ is defined by the total stress σ, the pore pressure p, and Biot coefficient α (a parameter controlling the pore pressure-stress interaction where 0<α<1) (Biot 1941):
ABSTRACT: Deformation features of rocks exhibit dependences on both strain rate and confinement, understanding dynamic mechanical behaviors of rocks under confinement conditions is of significance in dealing with various rock engineering fields, such as underground excavation, penetration and blasting. In this study, a novel Triaxial Hopkinson pressure bar was used to study the dynamic properties of rocks having a multi-axial stress state. Dynamic compression tests for sandstone are conducted over a wide range of impact velocities under different true tri-axial confined conditions. Experimental results demonstrate that the initial confining stress not only affects failure patterns but also leads to an increase of rock strength. Also, under the same confinement condition, the dynamic compressive strength and the failure behavior of rocks change with the increase of impact velocity. The couple effects of confining stress and strain rate on rocks properties can be studied and revealed. In addition, Synchrotron X-ray micro computed tomography (micro-μCT) technique was adopt to non-destructively detect and reconstruct the facture network of rocks after impact under confinement conditions, and the relationship between fracture plane and confining stresses is finally clarified.
Mechanical properties of rock material and rock mass under dynamic loads are significant parameters in rock structures (e.g. underground tunnels, cavities and mining roadways) design as well as disasters (e.g. rock bursts, landslides and earthquakes) prediction and control. They are also useful in providing basic information to study the propagation and attenuation of stress waves in geological medium (Li, 2010). Generally, prior to the frequent disturbance of dynamic loadings such as mechanical excavation, blasting, explosion and earthquake, both natural and engineering rocks are subjected to a state of existing geo-stresses, especially in true tri-axial pre-stresses (principal stresses σ1≥σ2≥σ3≠0) (Brown, 1978; Sharma, 2005; Liu et al., 2014). Therefore, it is necessary to study the dynamic behavior of rocks under different confined conditions at high loading rates.
ABSTRACT: This work presents results on grain scale cracking behaviors, inhomogeneous deformation and fracture process zone of Australian Harcourt granite under tensile conditions. Brazilian test was performed with cracking initiation and propagation being monitored by a high speed camera (2×105 frames/s). Digital image correlation (DIC) was utilized to obtain full-field kinetics and, the development of fracture process zone was characterized using an extended DIC algorithm. The obtained real-time information was further cooperated with the distribution of mineral grains obtained by the synchrotron micro CT and the digital photograph of crack surfaces. The initiative location and the interaction between the micro-cracking process and mineral grains were identified and analyzed. It is found that the first crack initiates on a quartz grain near a biotite particle with some deviation away from the disc geometrical center. Besides, biotite grains trend to deviate or arrest micro cracks resulting from the cleavage structure and higher ductility. The fracture process zone presents as a narrow band whereas it occurs and develops prior to visible cracks.
Rock as a dominant material forms the earth’s crust and has been the medium for many applications such as enhanced geothermal system, nuclear waste disposition, tunneling, excavation and forecast of earthquake. These issues are highly related to rock mechanical behaviors thus to understand the underlying mechanisms is of wide significance. Previous studies show that extent of heterogeneity varies in different rocks and some categories of rock behave differently from a homogenous solid (Chen, Yue, and Tham 2004; Chen et al. 2004; Mahabadi, Tatone, and Grasselli 2014).
Granite rock, as a dominant crystalline rock, has been intensely investigated. Due to the coarse sizes of grains with distinct mineral types, a strong grain scale heterogeneity exists. Many researchers have studied the influence of grain scale heterogeneity over mechanical strength, deformation and micro cracking behaviors of crystalline rock by means of micro computerized tomography (micro CT) (Nasseri, Rezanezhad, and Young 2011) , scanning electron microscopy (SEM) (Nasseri, Rezanezhad, and Young 2011; Schedl, Kronenberg, and Tullis 1986) and numerical simulation (Chen, Yue, and Tham 2004; Chen et al. 2004; Mahabadi, Tatone, and Grasselli 2014). They found that the deformation and damage behavior of this rock are largely affected by the grain-scale heterogeneity which includes mineral composition, grain size distribution, morphology of grain interfaces, and micro-defects. Both inter- and intro granular cracks can be induced as crystalline rock undergoes external load. However, as a crack in rock occurs and propagates generally in a very short time at laboratory scale, few work captured the real time deformation histories of deformation and cracking behaviors.
Visual inspection is a vital component of asset management that stands to benefit from automation. Using artificial intelligence to assist inspections can increase safety, reduce access costs, provide objective classification, and integrate with digital asset management systems. The work presented herein investigates the impact of dataset size on Deep Learning for automatic detection of corrosion on steel assets. Dataset creation is typically one of the first steps when applying Machine Learning methods to a new task; and the real-world performance of models hinges on the quality and quantity of data available. Producing an image dataset for semantic segmentation is resource intensive, particularly for specialist subjects where class segmentation is not able to be effectively farmed out. The benefit of producing a large, but poorly labelled, dataset versus a small, expertly segmented dataset for semantic segmentation is an open question. Here we show that a large, noisy dataset outperforms a small, expertly segmented dataset for training a Fully Convolutional Network model for semantic segmentation of corrosion in images. A large dataset of 250 images with segmentations labelled by undergraduates and a second dataset of just 10 images, with segmentations labelled by subject matter experts were produced. The mean Intersection over Union and micro F-score metrics were compared after training for 50,000 epochs. The relationship between dataset size and F-score was investigated to estimate the requirements to achieve human level accuracy. This work is illustrative for researchers setting out to develop deep learning models for detection and location of specialist features.
Corrosion is a difficult subject to detect compared to other common subjects such as the human face that have distinct features: two eyes, a nose and a mouth; corrosion shares limited characteristics in colour range and texture - and the appearance of corrosion is confused on both counts, with shadows, boulders, bricks, safety vests all presenting false positives for Deep Convolutional Neural Network (D-CNN) models. Furthermore, the boundary between corroded and uncorroded areas in images is often undefined, due to image compression artefacts and focal range (depth of field).
Proppant plays a vital role in hydraulic fracturing in tight oil/gas production because it helps to keep the fractures open during the production process. However, it is common for proppant embedment, the main type of proppant degradation, to occur under high compression load, which greatly reduces the fracture conductivity, and consequently reduces the production rate. During the process of hydraulic fracturing, the fracturing fluid only has the chance to contact and infiltrate the fractures that are in the top surface of the rock medium because of ultralow rock permeability and the short time of fluid existence, whereas the condition of other parts of the rock remain unchanged, creating inhomogeneity within the rock medium. Therefore, the present study conducted a comprehensive experimental and numerical evaluation to investigate the behavior of proppant for inhomogeneous rock media, considering the factors (effective stress, proppant concentration, and fracturing fluid) that affect proppant performance. According to the experimental results, increasing the proppant concentration reduces the proppant embedment, and, interestingly, the optimal proppant concentration is approximately 150% coverage. Furthermore, the influence of fracturing fluid on proppant embedment is more significant for high proppant concentrations, and the embedment under water-saturated conditions is higher than that under oil-saturated conditions. The numerical simulation achieved the same result as the experimental study, showing that 150% proppant coverage is the optimal proppant concentration to achieve the minimum proppant embedment. In addition, numerical modeling indicated that the inhomogeneity of the rock formation can also considerably enhance proppant embedment through differential settlement during compression.