<p> Rock fracture mechanics theories have been used for more than 50 years in the oil and gas industry. Fracture mechanics is about understanding what will happen to the rocks in the subsurface when subjected to fracture stress. Much of what is used in hydraulic fracturing theory and design was developed by other engineering disciplines many years ago. However, rock formations often cannot be treated as isotropic and homogeneous. These assumptions affect the calculation of in-situ stresses which are important for designing hydraulic fracture and knowing the stability of wellbore. A Geomechanical model is built to investigate these problems and to predict the alterations and changes of the Geomechanical properties of the reservoir. </p><p> After the reservoir characterization and determination of the magnitude and direction of in&ndash;situ stresses, our next step is to prepare a 3-D Geomechanical model in ANSYS Workbench. Elastic anisotropy of the formation is included in the 3-D numerical models. The model will represent the Bakken Formation, having all its properties. After preparing a mesh for this model to carry out further studies, we apply stresses to the model so that it represents the depth at which the Bakken Formation is encountered while keeping the drilling conditions in mind. We analyze wellbore stability and predict wellbore behavior under stress alteration caused by drilling. </p><p>

<p> In shale gas development, the mechanical properties of shale are crucial in hydraulic fracture propagation, wellbore stability, and the productivity of a shale gas wells. In this dissertation, acoustic velocity tests, uniaxial compressive tests, and Brazilian tensile tests were conducted on Eagle Ford and Mancos shale to investigate gas shale mechanical properties, including dynamic mechanial properties and static mechanical properties (compressive and tensile mechanical properties). Water content, mineralogy, and anisotropic effects on shale mechanical properties were analyzed. </p><p> Ultrasonic velocity measurements were performed on Eagle Ford shale samples. Dynaimic elastic properties were determined according to the compressive- and shear-wave vleocities. The results showed that both P- and S-wave velocities increase as confining pressure increases. Horizontal elastic modulus, vertical elastic modulus, and shear modulus increase with increasing confining pressure. While horizontal and vertical Poisson&rsquo;s ratio exhibited more or less invariant with confining pressure. Transverse isotropy is an appropriate model to characterize Eagle Ford gas shale. Elastic properties of Eagle Ford shale are direction-dependent. Horizontal Young&rsquo;s modulus is higher than vertical Young&rsquo;s modulus and horizontal Poisson&rsquo;s ratio is higher than vertical Poisson&rsquo;s ratio. Increasing water content reduce Young&rsquo;s modulus and shear modulus significantly. Induced water can make the shale softer. Water increase Eagle Ford shale&rsquo;s anisotropies. Both P- and S- wave velocities decrease with increasing of TOC and clay content. Dynamic Young&rsquo;s modulus, shear modulus, and bulk modulus vary inversely with TOC and clay. Poisson&rsquo;s ratio does not correlate with TOC or clay content for these test samples. </p><p> Static mechanical properties were investigated by conducting uniaxial compressive tests and Brazilian tensile tests on Eagle Ford and Mancos shale samples. A new method was developed to analyze tensile elastic behavior of materials. The imbibed water significantly reduces the uniaxial compressive strength. Young&rsquo;s modulus of wet samples is lower for corresponding dry samples. The maximum Young&rsquo;s modulus decrease is up to about 70%. The imbibed water makes the shale softer. Poisson&rsquo;s ratio increase with water content. Bedding plane/laminations have a significant impact on Eagle Ford indirect tensile strength, but not on Mancos shale. The imbibed water significantly reduces tensile strength and tensile Young&rsquo;s modulus, but increase tensile Poisson&rsquo;s ratio. Low clay content in the Eagle Ford shale (around 6%) and high clay content in the Mancos (around 22%) might be the explanation for the overall lower tensile strength of the Mancos than Eagle Ford shale. </p><p> Static and dynamic elastic properties of Eagle Ford shale samples are compared. Static Young&rsquo;s modululs is lower than dynamic Young&rsquo;s modulus. There is no strong correlations between static and dynamic Poisson&rsquo;s ratio observed for the tested samples. The relationship of compressive and tensile mechanical properties of Eagle Ford shale are investigated. Tensile Young&rsquo;s modululs is 0.76 to 0.98 times lower than corresponding compressive Young&rsquo;s modulus. There is either no strong correlations between tensile and compressive Poisson&rsquo;s ratio observed for the tested samples. </p><p> Water weaken mechanism was analyzed. Three potentially major weakening mechanisms&mdash;chemical effects, water clay interaction, and capillary pressure increase&mdash;were discussed in detail.</p><p>

<p> Reliability of equipment during well construction is necessary. Failure of components increases non-productive time and may cause injuries or loss of life. The jar is a component used in well construction, usually as part of the drill string to free stuck pipe or during fishing. It is subject to impact loads due to the hammering and tensile loads caused due to hook loads on the drill string. In this work, a root cause is failure analysis of failed component. The failure is different from all the other cases due to the reason that most of the time the component collapses and rather fails completely. The main objective is to find the root cause of failure. The visual inspection indicates signs of tensile and brittle failure. The scanning electron microscope analyses show evidence of fatigue: the classic beach mark striations. The presence of aluminum and voids in the section show that the material used for manufacture was of low quality. In this paper, efforts are made to provide recommendations to the company that rents these jars. The various causes of failure mentioned can be useful to have better understanding and control of the manufacturing process, improved instructions for the use of the jar, improve the overall reliability of the component, and use it for well construction with the safety of personnel and minimum non-productive time. </p><p>

<p> The use of surfactants to alter the reservoir hydrocarbons affinity towards the injection fluids such as water is an effective method to increase the oil production on depleted reservoirs. However, the actual field use of this technique has been limited by major economical complications generated by the unaccounted loss of surfactants to the reservoir rock pores. Reducing the adsorption of surfactants to the reservoir rock can be achieved through the addition of sacrificial elements to the injection slug. Sacrificial elements such as polymers can engage in a competitive behavior with surfactants for the adsorption to the reservoir rock surface. This thesis work focuses on the simulation of the dynamic adsorption of surfactants when sacrificial agents, such as polymers, are injected on a 3-D field scale reservoir model. </p><p> The purpose of this thesis research is to determine if the new in model for streamline particle flow simulation developed in-house for academic purposes can accurately predict the surfactant and polymer adsorption/desorption to the reservoir pores. Based on laboratory experiment data from publications, the SL simulator will model the surfactant and polymer adsorption on a 3-D heterogeneous reservoir in order to determine if the surfactant adsorption could be reduced when polymers are injected as sacrificial agents on a chemical mixture or sequential profile. The simulation output displays promising results, since it accurately models the effects generated on the surfactant dynamic adsorption caused by the injection of sacrificial agents such as polymers. This 3-D SL simulator could be used for field applications to obtain better predictions about the dynamic adsorption of surfactants, which would increase the efficiency of surfactant flooding operations.</p><p>

<p> Hydraulic fracturing is a commonly used practice in stimulation treatment, especially in low-permeability formation. The fracture complexity usually took place in relation to the interaction between fractures and natural rock fabrics. Despite many studies regarding the production simulation, diagnostic methods, and mathematical models about fracture complexity, research about the local complexity development is still needed for optimized stimulation design. Aiming to predict the local complexity development and stimulation performance, a hierarchy model is designed to make the problem more tractable, and a corresponding mathematical model is developed for numerical simulation. A case study is provided, and the comparison with the result of micro-seismic mapping indicates much discrepancy between field data and simulated result. Considering the many limitations of the model, the discrepancy is tolerable and acceptable. According to the sensitivity analysis, a high injection rate could serve to increase fracture complexity while reducing the maximum length of fractures. The sensitivity analyses regarding bottom-hole net pressure show a weak relationship between the fracture complexity and the bottom-hole net pressure, but a high injection pressure or low in-situ stress can serve to enhance the stimulation performance by increasing the maximum length of fractures. Sensitivity analyses for fluid properties indicate that using the high-viscosity fracturing fluid can add to the local complexity of fractures and reduce the maximum length of fractures, while fluid density has little to do with the fracture complexity and stimulation performance. The parametric study regarding rock surface energy indicates little effect of surface energy of different shale rocks on changing the local fracture complexity and stimulation performance.</p><p>

Data driven modeling (DDM) techniques implement machine learning (ML) to analyze data and discover connections without explicit knowledge of the physical behavior. Recent improvements in technology and computational power have increased interest in the application of DDM in petroleum industry. Recovery process evaluation using numerical reservoir simulators are always costly, time consuming, computational intensive with many assumptions and uncertainty involved. In this thesis, DDM have been adopted as an alternative tool to predict production performance under waterflooding which is one of the most important techniques for improving oil recovery. A synthetic waterflooding dataset including production profile, operational parameters, reservoir properties and well locations is constructed using the numerical reservoir simulator. Exploratory data analysis provides several insights into the non-intuitive factors in building the reservoir model. K-means clustering analysis is performed to identify internal groupings among producers. Artificial neural network (ANN) and support vector machine (SVM), particularly support vector regression (SVR), are used to decipher the nonlinear relationships between input attributes and waterflooding production. The trained models are subsequently used to predict cumulative oil and watercut on the unseen samples. Clustering analysis reveal that distance to the free water level has a dominant effect. The cluster that has the smallest average distance to FWL tends to have the highest watercut and lowest cumulative oil compared with the simulation results. Clustering results also indicates that the clustering assignment is controlled by the interplay among input attributes characterizing reservoir properties and relative well locations. Good agreements between predicted outputs from models and simulation targets present the satisfactory generalization performance and predictive capabilities of ANN and SVR methods. ANN model with one output provides the most accurate prediction result on the test data. ANN model with two outputs reveals the robustness of this approach. SVR models provide similar but slightly worse forecast than ANN models. No previous work studied on the application of SVM on waterflooding performance prediction. Results in this study verify its acceptability and applicability. Proposed methodologies in this thesis study can be utilized as a surrogate or complementary model to analyze and predict recovery process in other reservoirs fast and efficiently.

<p> Steam stimulation is by far the most widely used tertiary oil recovery method. Heavy oil finds its most effective way of production in thermal recovery method. Also with technical effectiveness, steam stimulation brings in cost effectiveness. In-situ steam generation and injection is the most important enhancement to the conventional thermal steam injection technique. Blackbird&trade; Energy LLC, has developed and a new generation in-situ steam generator with a view to make an almost unproductive heavy oil reservoir in North East Texas to start producing. </p><p> In this research, a reservoir simulation study has been performed to history match of pure depletion as well as three months of thermal stimulation done on the reservoir. To mimic the reservoir conditions, Schlumberger Eclipse 300 compositional Simulator has been used. Overall this research performs an evaluation of the newly developed in-situ steam generator capabilities. </p><p> The various predictive runs have been made with changing key performance parameters such as location of steam generator and time of application of thermal energy. There has been reported a considerable increase in production of the heavy oil. As a result, in-situ steam injection has been proved to be an effective and environment friendly recovery technique and should be widely considered for replacing conventional steam generators.</p>

<p>In order to develop and apply nanotechnology in oil industry, nanoparticles transport in porous media has been studied in the past few years. Theoretical modeling were carried out to evaluate nanoparticle mobility and investigate nanoparticle retention mechanism. In this study, a simulator based on Ju and Fan&rsquo;s mathematical model was used to study nanoparticles transport in porous media on a reservoir scale. The simulator was verified with two simulation software, Eclipse from Schlumberger and MNM1D (Micro- and Nanoparticle transport Model in porous media in 1D geometry) developed by Tosco et al. Different injection scenarios were simulated: continuous injection, slug injection, and postflush. The effect of injection time, injection rate, and slug size on oil recovery were studied. The result discovered that when nanofluids flooding is used after water flooding as tertiary recovery method, early nanofluids injection will lead to higher oil recovery, but with more nanoparticle loss. Higher injection rate of nanofluids could help improve the flooding efficiency, but not the ultimate oil recovery for field development. Also, it can cause more nanoparticle loss. Brine water postflush is recommended when doing nanoflooding. It can significantly improve the recovery of nanoparticles, and for a homogeneous or heterogeneous reservoir, oil recovery is better compared to water flooding. </p>

<p> This experiment was designed to study iron control systems in fracking and well stimulation jobs at higher pH. Experimental study of iron control at high pH of this kind has not previously been reported in the literature. In addition, almost all of the widely used iron control chemicals today work at lower pH (&le;4). </p><p> In this experiment, newly enhanced chemicals, such as EnerFlow 780, SC803, EDTA, Poly Itaconic acid, and TN801 were used and the following new result were found. In the absence of iron control chemicals, iron precipitation occurred at pH of 1.85 and completely precipitated at 3.5. <b>SC803</b> has shown a very unique characteristic. The chelating characteristic of this product increases with pH. At lower pH (&le;4), this product has shown weaker performance in curbing iron precipitation. Only 37% (average) initial iron was prevented from precipitating at this pH. However, when the pH was increased to above 4, its sequestering characteristic became more and more until it reached pH 13. Minimum precipitation was observed at pH of 11 &amp; 12, which are 4.3% and 4.7%, respectively. Furthermore, SC803 was observed to cause unforeseen yellowish iron precipitation at lower pH. </p><p> <b>TN801,</b> a blend of SC803, EDTA and Poly Itaconic acid, showed the best result of the all the individual chemicals tested. It effectively curbed an average of 96% iron precipitation in all pH less than 13. EDTA and Poly Itaconic acid were added to enhance the performance of SC803 at lower pH. The result showed 86.8% maximum enhancement at lower pH and 0.3% at higher pH. TN801 was also able to dissolve 50% of crystalline iron sulfide, despite the fact that it is insoluble in nature. Furthermore, TN801 was tested on field and the anticipated result was achieved.</p>

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