Reservoir Characterization and Waterflood Performance Evaluation of Granite Wash Formation, Anadarko Basin

The Granite wash formation in the Anadarko basin is classified as a tight-gas play and is located along the Texas – Oklahoma border. It has a complex mineralogy and consists of stacked-pay series of tight sands. Our zone of interest is the liquid-rich Missourian Wash B interval in Wheeler County in which two horizontal wells have been drilled. The purpose of this research is to characterize the reservoir through geologic modeling and determine the feasibility of a waterflood using simulation studies. A set of field data was provided by the operator and other necessary parameters were obtained through publicly available field studies and literature. The final objective is implementing advanced reservoir simulation to integrate well log data, PVT data, diagnostic fracture injection test and microseismic analysis into a plan of development. The Missourian Wash B formation has a maximum net pay thickness of 50ft. The target sand is laterally continuous which makes it an ideal horizontal drilling prospect. The wells are stimulated by multi-stage hydraulic fracturing. The initial production gas-oil ratio is 1800 scf/stb and PVT reports indicate presence of an oil reservoir above bubble point pressure. PVT correlations show that the 42º API oil and potential injection water at the reservoir temperature have almost the same viscosity. All these factors point towards the formation being a good waterflood candidate. Well log analysis was performed to obtain porosity and saturation estimates. The microseismic mapping report provides a good overview of the well completion efficiency. Laboratory PVT data was tuned to predict reservoir fluid behavior by parameter regression and component lumping. An isotropic black-oil simulator by Computer Modeling Group Ltd was selected for our work. The reservoir model was validated by sensitivity studies and history matching of production rates was performed. Simulation result of waterflood implementation by utilizing offset horizontal wells as injectors is analyzed, and three different plans of development are discussed. It is seen that the overall response to waterflooding is poor due to low formation permeability leading to low water injectivity. But a greater reservoir area can be drained if production is initiated from additional horizontal wells. A well-spacing of four horizontal wells in 600 acres section is recommended. The stimulated reservoir volumes of adjacent wells should be close to each other for effective reservoir drainage

Reservoir Characterization and Waterflood Performance Evaluation of Granite Wash Formation, Anadarko Basin

The Granite wash formation in the Anadarko basin is classified as a tight-gas play and is located along the Texas – Oklahoma border. It has a complex mineralogy and consists of stacked-pay series of tight sands. Our zone of interest is the liquid-rich Missourian Wash B interval in Wheeler County in which two horizontal wells have been drilled. The purpose of this research is to characterize the reservoir through geologic modeling and determine the feasibility of a waterflood using simulation studies. A set of field data was provided by the operator and other necessary parameters were obtained through publicly available field studies and literature. The final objective is implementing advanced reservoir simulation to integrate well log data, PVT data, diagnostic fracture injection test and microseismic analysis into a plan of development. The Missourian Wash B formation has a maximum net pay thickness of 50ft. The target sand is laterally continuous which makes it an ideal horizontal drilling prospect. The wells are stimulated by multi-stage hydraulic fracturing. The initial production gas-oil ratio is 1800 scf/stb and PVT reports indicate presence of an oil reservoir above bubble point pressure. PVT correlations show that the 42º API oil and potential injection water at the reservoir temperature have almost the same viscosity. All these factors point towards the formation being a good waterflood candidate. Well log analysis was performed to obtain porosity and saturation estimates. The microseismic mapping report provides a good overview of the well completion efficiency. Laboratory PVT data was tuned to predict reservoir fluid behavior by parameter regression and component lumping. An isotropic black-oil simulator by Computer Modeling Group Ltd was selected for our work. The reservoir model was validated by sensitivity studies and history matching of production rates was performed. Simulation result of waterflood implementation by utilizing offset horizontal wells as injectors is analyzed, and three different plans of development are discussed. It is seen that the overall response to waterflooding is poor due to low formation permeability leading to low water injectivity. But a greater reservoir area can be drained if production is initiated from additional horizontal wells. A well-spacing of four horizontal wells in 600 acres section is recommended. The stimulated reservoir volumes of adjacent wells should be close to each other for effective reservoir drainage

Reducing the uncertainty of thermal model calibration using on-machine probing and data fusion

Various sources of error hinder the possibility of achieving tight accuracy requirements for high-value manufacturing processes. These are often classified as: pseudo-static geometric errors; non-rigid body errors; thermal errors; and dynamic errors. It is comparatively complicated to obtain an accurate error map for the thermal errors because they are influenced by various factors with different materials, time constants, asymmetric heating sources and machining process, environmental effects, etc. Their transient nature and complex interaction mean that they are relatively difficult to compensate using pre-calibration methods. For error correction, the magnitude and sign of the error must first be measured or estimated. Pre-calibrated thermal compensation has been shown to be an effective means of improving accuracy. However, the time required to acquire the calibration data is prohibitive, reducing the uptake of this technology in industrial applications. Furthermore, changing conditions of the machine or factory environment are not adequately accommodated by pre-calibrated compensation, leading to degradation in performance. The supplementary use of on-machine probing, which is often installed for process control, can help to achieve better results. During the probing operation, the probe is carried by the machine tool axes. Therefore, the measurement data that it takes inevitably includes both the probing errors and those originating from the inaccuracies of a machine tool as well as any deviation in the part or artefact being measured. Each of these error sources must be understood and evaluated to be able to establish a measurement with a stated uncertainty. This is a vital preliminary step to ensure that the calibration parameters of the thermal model are not contaminated by other effects. This thesis investigates the various sources of measurement uncertainties for probing on a CNC machine tool and quantify their effects in the particular case where the on-machine probing is used to calibrate the thermal error model. Thermal errors constitute the largest uncertainty source for on-machine probing. The maximum observed thermal displacement error was approximately 220 μm for both X and Z-axis heating test at 100 % speed. To reduce the influence of this uncertainty source, sensor data fusion model using artificial neural network and principal component analysis was developed. The output of this model showed better than 90 % correlation to the measured thermal displacement. This data fusion model was developed for the temperature and FBG sensors. To facilitate the integration of the sensor and to ease the communication with machine tool controller, a modular machine tool structural monitoring system using LabVIEW environment was developed. Finally, to improve the performance of the data fusion model in order to reduce the thermal uncertainty, a novel photo-microsensor based sensing head for displacement measurement is presented and analysed in detail. This prototype sensor has measurement range of 20 μm and resolution of 21 nm

Vascular endothelial growth factor-A (VEGF-A) and chemokine ligand-2 (CCL2) in Amyotrophic Lateral Sclerosis (ALS) patients

Correction to Gupta P K, Prabhakar S, Sharma S, Anand A. Vascular endothelial growth factor-A (VEGF-A) and chemokine ligand-2 (CCL2) in amyotrophic lateral sclerosis (ALS) patients. Journal of Neuroinflammation 8:47