The main parameter that drives oil industry contract investment and set up economic feasibility study for approving field development plan is hydrocarbon reservoir potential. So a qualified experience should be deeply afforded to correctly evaluate hydrocarbons reserve by applying different techniques at each phase of field management, through collecting and using valid and representative data sources, starting from exploration phase and tune-up by development phase. Commonly, volumetric calculation is the main technique for estimate reservoir potential using available information at exploration stage which is quite few data; in most cases, this technique estimate big figure of reserve. In this study case, volumetric calculation estimate gas initial in place (GIIP) value almost two times bigger than other techniques estimation of actual reservoir potential; it is a result of Asphiltena “Bitumen” existing in reservoir interval which occupied part of matrix pore and fill some fractures. This investigation is raised up at early field production life: material balance calculation and run simulation analysis are applied to re-assessment and tune-up reservoir potential; both techniques are set up almost same GIIP value which principally tuned to actual reservoir dynamic energy behavior. Finally, material balance should be viewed as a complement to simulation, not as a competing approach, and using both to improve analysis of hydrocarbon reservoirs.
Accounting disclosure is the main means and effective tool for communicating business results to users in support of their decisions, especially those with thought and specialization from academics and professionals in the field of accounting and auditing about the importance of accounting disclosure and transparency in financial reports.
Contingent liabilities represent commitments based on the occurrence of one or more events in the future to confirm the value due, the party entitled to it, the maturity date, or to confirm the existence of the obligation itself, and therefore they should not be recognized as a contingent liability i
... Show MoreThe Boltzmann equation has been solved using (EEDF) package for a pure sulfur hexafluoride (SF6) gas and its mixtures with buffer Helium (He) gas to study the electron energy distribution function EEDF and then the corresponding transport coefficients for various ratios of SF6 and the mixtures. The calculations are graphically represented and discussed for the sake of comparison between the various mixtures. It is found that the various SF6 – He content mixtures have a considerable effect on EEDF and the transport coefficients of the mixtures
A hybrid Gas-Enhanced and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been suggested to enhance oil recovery by placing vertical injectors for CO2 at the top of the reservoir with a series of horizontal oil-producing and water-drainage wells located above and below the oil-water contact, respectively. The injected gas builds a gas cap that drives the oil to the (upper) oil-producing wells while the bottom water-drainage wells control water cresting. The hybrid process of GDWS-AGD process has been first developed and tested in vertical wells to minimize water cut in reservoirs with bottom water drive and strong water coning tendencies. The wells were dual-compl
Mature oil reservoirs surrounded with strong edge and bottom water drive aquifers experience pressure depletion and water coning/cresting. This laboratory research investigated the effects of bottom water drive and gas breakthrough on immiscible CO2-Assisted Gravity Drainage (CO2-AGD), focusing on substantial bottom water drive. The CO2-AGD method vertically separates the injected CO2 to formulate a gas cap and Oil. Visual experimental evaluation of CO2-AGD process performance was performed using a Hele-Shaw model. Water-wet sand was used for the experiments. The gas used for injection was pure CO2, and the “oleic” phase was n-decane with a negative spreading coefficient. The aqueous phase was deionized water. To evaluate the feasibilit
... Show MoreThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo
The problem of dark matter in galaxies is still one of the most important unsolved problems in the contemporary extragalactic astronomy and cosmology. The existence of a significant dynamic difference between the visible mass and the conventional mass of galaxies firmly establishes observational result. In this paper an unconventional explanation will be tested as an alternative to the cold dark matter hypothesis; which is called the modified Newtonian dynamics (MOND).
In this paper covers the simulation of galactic evolutions; where the two hypotheses are tested via the rotation curves. N-body simulation was carried adopting different configuration lik
This study aims to numerically simulate the flow of the salt wedge by using computational fluid dynamics, CFD. The accuracy of the numerical simulation model was assessed against published laboratory data. Twelve CFD model runs were conducted under the same laboratory conditions. The results showed that the propagation of the salt wedge is inversely proportional to the applied freshwater discharge and the bed slope of the flume. The maximum propagation is obtained at the lowest discharge value and the minimum slope of the flume. The comparison between the published laboratory results and numerical simulation shows a good agreement. The range of the relative error varies between 0 and 16% with an average of 2% and a roo
... Show MoreThe main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
... Show MoreAqueous root extract has been used to examine the green production of silver nanoparticles (AgNPs) by reducing the Ag+ ions in a silver nitrate solution. UV-Vis spectroscopy, X-ray diffraction, field emission scanning electron microscopy, and Fourier transform infrared spectroscopy (FTIR) were used to analyze the produced AgNPs. The AgNPs that were created had a maximum absorbance at 416 nm, were spherical in form, polydispersed in nature, and were 685 nm in size.The AgNPs demonstrated antibacterial efficacy against Escherichia coli and Staphylococcus. The dengue vector Aedes aegypti's second instar larvae were very susceptible to the AgNPs' powerful larvicidal action.
Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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