Browsing by Subject "forecasting"
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Item A New Method for History Matching and Forecasting Shale Gas/Oil Reservoir Production Performance with Dual and Triple Porosity Models(2012-10-19) Samandarli, OrkhanDifferent methods have been proposed for history matching production of shale gas/oil wells which are drilled horizontally and usually hydraulically fractured with multiple stages. These methods are simulation, analytical models, and empirical equations. It has been well known that among the methods listed above, analytical models are more favorable in application to field data for two reasons. First, analytical solutions are faster than simulation, and second, they are more rigorous than empirical equations. Production behavior of horizontally drilled shale gas/oil wells has never been completely matched with the models which are described in this thesis. For shale gas wells, correction due to adsorption is explained with derived equations. The algorithm which is used for history matching and forecasting is explained in detail with a computer program as an implementation of it that is written in Excel's VBA. As an objective of this research, robust method is presented with a computer program which is applied to field data. The method presented in this thesis is applied to analyze the production performance of gas wells from Barnett, Woodford, and Fayetteville shales. It is shown that the method works well to understand reservoir description and predict future performance of shale gas wells. Moreover, synthetic shale oil well also was used to validate application of the method to oil wells. Given the huge unconventional resource potential and increasing energy demand in the world, the method described in this thesis will be the "game changing" technology to understand the reservoir properties and make future predictions in short period of time.Item A Study of Decline Curve Analysis in the Elm Coulee Field(2013-08-22) Harris, Seth CIn the last two years, due in part to the collapse of natural gas prices, the oil industry has turned its focus from shale gas exploration to shale oil/tight oil. Some of the important plays under development include the Bakken, Eagle Ford, and Niobrara. New decline curve methods have been developed to replace the standard Arps model for use in shale gas wells, but much less study has been done to verify the accuracy of these methods in shale oil wells. The examples that I investigated were Arps with a 5% minimum decline rate as well as the stretched exponential model (SEPD) and the Duong method. There is a great amount of uncertainty about how to calculate reserves in shale reservoirs with long multi-fractured horizontals, since these wells have not yet been produced to abandonment. Although the Arps model can reliably describe conventional reservoir production decline, it is still uncertain which empirical decline curve method best describes a shale oil well to get a rapid assessment of expected recovery. My focus began in the oil window of the Eagle Ford, but I ultimately chose to study the Elm Coulee field (Bakken formation) instead to see what lessons an older tight oil play could lend to newer plays such as the Eagle Ford. Contrary to existing literature, I have found evidence from diagnostic plots that many horizontal wells in the Elm Coulee that began producing in 2006 and 2007 have entered boundary-dominated flow. In order to accommodate boundary flow I have modified the Duong and SEPD methods such that once boundary-dominated flow begins the decline is described by an Arps curve with a b-value of 0.3. What I found from hindcasting was that early production history, up to six months, is generally detrimental to accurate forecasting in the Elm Coulee. This was particularly true for the Arps with 5% minimum decline or the Duong method. Early production history often contains apparent bilinear flow or no discernible trend. There are many possible reasons for this, particularly the rapid decrease in bottomhole pressure and production of fracture fluid.Item Multi-Scale Conservation in an Altered Landscape: The Case of the Endangered Arroyo Toad in Southern California(2014-07-18) Treglia, Michael LouisHabitat loss and degradation are recognized as significant drivers of biodiversity loss in terrestrial and freshwater ecosystems. These issues are often associated with anthropogenic land cover changes, which can have direct and indirect impacts on species, and conservation strategies must take both into account for long-term success. I focused this dissertation on the endangered arroyo toad (Anaxyrus califonicus), endemic to southern California, USA and northern Baja California, Mexico. The species relies on open, sandy streams for breeding and larval development, and the adjacent terrestrial environments for post-metamorphosis life stages; primary threats include destruction and degradation of these habitats. I conducted three studies to better understand threats to, and identify conservation opportunities for arroyo toads in southern California. First, I developed distribution models that enabled me to identify areas that could be used to create habitat for the species, which could then be colonized by nearby populations or populated via translocation efforts. Second, I used structural equation modeling to investigate relationships among land cover characteristics at multiple spatial scales and suitability of riparian areas for arroyo toads. This study yielded insight into how land cover of entire watersheds and along stream networks influence arroyo toad habitat. Lastly, I used a structural equation model in conjunction with a projection of development for my study area to forecast how future urbanization may influence suitability of habitats for arroyo toads in individual watersheds. I compared results for scenarios with high and low levels of urbanization, and found conservation of natural land covers at the watershed scale can ultimately help maintain habitat in the long-term. The results of these studies may guide both immediate and future conservation efforts for arroyo toads in my study area. My approaches can be applied to other systems for understanding conservation issues affecting other species. Furthermore, future work may build on this research to inform conservation in other parts of the arroyo toad?s range, and models can be iteratively improved as land cover changes occur and the species responds through time.Item Observations, dynamics and predictability of the mesoscale convective vortex event of 10-13 June 2003(Texas A&M University, 2006-08-16) Hawblitzel, Daniel PatrickThis study examines the dynamics and predictability of the mesoscale convective vortex (MCV) event of 10-13 June 2003 which occurred during the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX). The MCV formed from a preexisting upper-level disturbance over the southwest United States on 10 June and matured as it traveled northeastward. The BAMEX field campaign provided a relatively dense collection of upper air observations through dropsondes on 11 June during the mature stage of the vortex. While several previous studies have focused on analysis of the dynamics and thermodynamics of observed and simulated vortices, few have addressed the ability to predict MCVs using numerical models. This event is of particular interest to the study of MCV dynamics and predictability given the anomalously strong and long-lived nature of the circulation and the dense data set. The first part of this study explores the dynamics of this MCV through an in-depth analysis of data from the profiler network and BAMEX dropsonde observations, in addition to the conventional surface and sounding observations as well as radar and satellite images. Next, issues relating to model performance are addressed through anevaluation of two state-of-the-art mesoscale models with varying resolutions. It is determined that the ability of a forecast model to accurately predict this MCV event is directly related to its ability to simulate convection. It is also shown that the convective-resolving Weather Research and Forecast (WRF) model with horizontal grid increments of 4 km displays superior performance in its simulation of this MCV event. Finally, an ensemble of 20 forecasts using mesoscale model MM5 with horizontal grid increments of 10 km are employed to evaluate probabilistically the dynamics and predictability of the MCV through the examination of the ensemble spread as well as the correlations between different forecast variables among ensemble members. It is shown that after MCV development, the ensemble mean performs poorly while individual ensemble members with good forecasts of convection at all stages of the MCV also forecast the midlevel vortex well. Furthermore, correlations among ensemble members generally support the findings in the observational analysis and in previous literature.Item Optimization of a petroleum producing assets portfolio: development of an advanced computer model(2009-05-15) Aibassov, GizatullaPortfolios of contemporary integrated petroleum companies consist of a few dozen Exploration and Production (E&P) projects that are usually spread all over the world. Therefore, it is important not only to manage individual projects by themselves, but to also take into account different interactions between projects in order to manage whole portfolios. This study is the step-by-step representation of the method of optimizing portfolios of risky petroleum E&P projects, an illustrated method based on Markowitz?s Portfolio Theory. This method uses the covariance matrix between projects? expected return in order to optimize their portfolio. The developed computer model consists of four major modules. The first module generates petroleum price forecasts. In our implementation we used the price forecasting method based on Sequential Gaussian Simulation. The second module, Monte Carlo, simulates distribution of reserves and a set of expected production profiles. The third module calculates expected after tax net cash flows and estimates performance indicators for each realization, thus yielding distribution of return for each project. The fourth module estimates covariance between return distributions of individual projects and compiles them into portfolios. Using results of the fourth module, analysts can make their portfolio selection decisions. Thus, an advanced computer model for optimization of the portfolio of petroleum assets has been developed. The model is implemented in a MATLAB? computational environment and allows optimization of the portfolio using three different return measures (NPV, GRR, PI). The model has been successfully applied to the set of synthesized projects yielding reasonable solutions in all three return planes. Analysis of obtained solutions has shown that the given computer model is robust and flexible in terms of input data and output results. Its modular architecture allows further inclusion of complementary ?blocks? that may solve optimization problems utilizing different measures (than considered) of risk and return as well as different input data formats.Item Radar Nowcasting of Total Lightning over the Kennedy Space Center(2011-08-08) Seroka, Gregory NicholasThe NASA Kennedy Space Center (KSC) is situated along the east coast of central Florida, where a high frequency of lightning occurs annually. Although cloud-to-ground (CG) lightning forecasting using radar echoes has been thoroughly analyzed, few studies have examined intracloud (IC) and/or total (IC CG) lightning. In addition to CG lightning, IC flashes are of great concern to KSC launch operations. Four years (2006-2009) of summer (June, July, August) daytime (about 14-00 Z) Weather Surveillance Radar ? 1988 Doppler data for Melbourne, FL were analyzed. Convective cells were tracked using a modified version of the Storm Cell Identification and Tracking (SCIT) algorithm and then correlated to CG lightning data from the National Lightning Detection Network (NLDN), as well as grouped IC flash data acquired from the KSC Lightning Detection and Ranging (LDAR) networks I and II. Pairs of reflectivity values (30, 35, and 40 dBZ) at isothermal levels (-10, -15, -20 and updraft -10 degrees C), as well as a vertically integrated ice (VII) product were used to optimize criteria for radar-based forecasting of both IC and CG lightning within storms. Results indicate that the best radar-derived predictor of CG lightning according to CSI was 25 dBZ at -20 degrees C, while the best reflectivity at isothermal predictor for IC was 25 dBZ at -15 degrees C. Meanwhile, the best VII predictor of CG lightning was the 30th percentile (0.840 kg m-2), while the best VII predictor of IC was the 5th percentile (0.143 kg m-2), or nearly 6 times lower than for CG! VII at both CG and IC initiation was higher than at both CG and IC cessation. VII was also found to be lower at IC occurrence, including at initiation, than at CG occurrence. Seventy-six percent of cells had IC initiation before CG initiation; using the first IC flash as a predictor of CG occurrence also statistically outperformed other predictors of CG lightning. Even though average lead time for using IC as a predictor of CG was only 2.4 minutes, when taking into account automation processing and radar scan time for the other methods, lead times are much more comparable.