The Oil Industry

Houston, which is the fourth most populous city in the nation and the largest in the southern U.S. and Texas, has been developing strong economy, especially in oil and gas industry. During the last decades of the twentieth century, Houston focused on developing energy industry—which comprises oil and gas exploration and production, oilfield equipment manufacturing and wholesaling, and pipeline transportation. However, some economists doubt that depending on oil and gas too much could make Houston particularly vulnerable to economic downturns determined by energy prices, the national economy, and the value of the dollar against foreign currencies. In fact, oil and gas have driven the Houston economy and been responsible for 50% of the jobs related to the export of goods and services outside the area. This research focuses on analyzing some factors including the incentive programs (local and state policies about taxation) and state organizations including the Texas General Land Office and the Texas Railroad Commission as contributions to regulate and organize oil and gas industry in order to develop Houston economy healthily and prosperously. Besides that, facts and figures from secondary resources are showed as achievements of Houston in developing economy depending on oil and gas industry. Clearly, thanks to state and local policies and programs as well as these state organizations in oil and gas industry, Houston is a potential economy region whose economy is growing faster

\KwIn{nodal value of solution $\mathbf{u} = \left(p, \mathbf{v} \right)$, volume geometric factors $\partial (rst)/ \partial (xyz)$, 1D derivative operator $D_{ij} = \partial \hat{l}_j /\partial x_i$, model parameters $\rho, c$}

This assignment is written in fulfillment of the MKT/421 class at the University of Phoenix. The assignment calls for covering each of the three major phases in the simulation and to describe:

Civica will first create the model for future conditions based on the calibrated model. This will involve adding proposed ponds and changing parameter values to reflect the future developments (e.g. imperviousness and curve number).

If applicable, change any variables, record them below, run the simulation, and record your results in the following data table:

Tobias  Vogel   1. TITLE Assignment  2  –  Everest  simulation   MGMT1001  

The main components in the process are the hydraulic fracturing pumps. Controllers must be used for proper operation. The main solution used for this process is water. When the hydraulic fracturing procedure starts flow rate, pressure and volume are both monitored. Volume must be monitored due to the strict freshwater usage requirements, Directive 55 states specifics depending on location, therefore needing volumetric flow meters (Alberta Energy Regulators, 2001). Once pressure is achieved a pressure versus flow profile is created to give operators a precise indication of pressure build up, and progress towards fracture. Internal rock formation pressure causes fracture fluids to return to the surface where they are known as flow-back

Under the guidance of Dr. Zenon Medina-Cetina, director of SGL, I did an extensive literature review and wrote a primary honors thesis on the geologic assessment of different drilling, completion, and stimulation methods in selected gas shale plays worldwide. This research experience made me realize a multi-disciplinary approach to different problems faced by the gas shale industry, and helped me broaden my knowledge of quantitative seismology applications in the gas shale industry.

Economically, operators of the gas field have an incentive to maintain fractures in the gas producing shale. Extending the fractures into a surrounding formation might allow saline fluids or brines to enter the induced fracture and flow into the gas producing portion of the shale, which could significantly hamper gas production. Even if hydraulically induced fractures extend into overlying formations, the possibility for fluids to leak upward into an aquifer is remote, unless those fractures are also connected to some other pathway,

During the experiment, the solution was agitated at 350rpm for two flow rates, 80 mL/min and 100 mL/min . As seen in Figure 1, the 100mL/min flow rate solution dropped in pH faster than the solution with a 80 mL/min flow rate. This was due to the solution not being saturated at 80mL/min and able to conduct a chemical reaction. Another important observation was that due to the lack of data, some of the trends had to be predicted for both flow rates. This can be observed in Figure 2 and Figure 3. Subsequently, it was predicted that the higher flow rate would have had a steeper slope.

Hydraulic Fracturing is a controversial method by which we are able to obtain natural gas from subterranean natural reservoirs within the earth. This process requires a shaft to be drilled vertically below the ground, and once a target depth has been reached below fresh water aquifers, horizontal drilling can occur. A long this horizontal shaft, the wellbore, a high pressurized mixture of water, chemicals, and sand is injected in order to create fractures in the oil and gas reservoirs within the rock. When the pump pressure is relieved, sand particles are left behind which keep the fractures open, providing an outlet for the natural gas to be collected. This process can produce oil or natural gas for twenty to forty years or more

A SWAT model for simulation under surface flow using from the reserve kinetic model. This model simulation subsurface flow in tow-dimensional section and flow down the slope that calculation from Equation (5).

The inflow into the tank was then graphed to show the Inflow vs. Time, the results obtained had some outliers in the initial negative trend so a linear interpolation of the part of the data set

This project will focus on the dynamics of capillary bridge formation and breakup in order to obtain a

Based on the full linear model and as shown in Figure ~\ref{fig:sa1lm}, the reservoir porosity factor has no effect on the flow response as it has horizontal line of residual. Figure ~\ref{fig:sa1_lm} shows the basic diagnostic plots for the full linear model. The residuals vs. fitted plot is used to determine if the linear relationship between the predictor variables and outcome variables are captured by the model. An accurate model will have a residuals vs. fitted plot with a horizontal line with residuals above and below it without forming a patterns or groupings, as seen in the top left plot. The normal Q-Q plot, shown in the top right plot, is used to determine if the residuals are normally distributed. A good normal distribution will have a normal Q-Q plot which follows a straight line, as do our results. The Scale-Location plot shows if the residuals are spread equally along all ranges of the predictors. Ideally, the residuals should be randomly spread across all fitted values and not trend to one area, as ours do in the bottom left plot. Lastly, the Residuals vs Leverage plot determines how big of an impact outliers points have on the regression curve. Outliers away from the Cook’s distance will have a large impact, while those nearby will not. The bottom right plot shows that all but 3 residuals are