LEE- Petrol ve Doğal Gaz Mühendisliği-Yüksek Lisans

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http://hdl.handle.net/11527/19423

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Artificial neural network tool development for flue gas sequestration in depleted shale oil reservoirs

(Graduate School, 2023-01-27) Bilim, Yasin Burak ; Kulga, Burak ; 505191511 ; Petroleum and Natural Gas Engineering

The energy needs of societies are increasing day by day. Oil and natural gas use have become more common with developing technology to meet this demand. However, this consumption also brings some concerns. The negative effects of fossil fuels on the environment, especially greenhouse gas (CO2, CO, N2O, H2S) emissions, have become a cause for worry. Today, the concentration of carbon dioxide in the atmosphere is increasing. Sequestration of flue gas released from factories and power plants is one of the methods used to reduce the rate of greenhouse gases in the atmosphere. In this study, an artificial neural network (ANN) tool that predicts the sequestration of flue gas has been developed. With the developed tool, production estimation can be made for hydraulically fractured shale oil reservoirs with horizontal wells in addition to the flue gas injection time and pressure. The reservoir model used in this study has some key features, such as the stimulated reservoir volume approach, the double porosity double permeability phenomenon and Langmuir adsorption isotherm formulation. After creating the desired reservoir model, minimum and maximum value ranges were taken from the literature for reservoir characteristics and operational parameters. According to these intervals, 10,000 different models with normal distribution were generated randomly and simulated with the CMG GEM simulator. Randomly generated scenario variables and obtained results from the simulation were used in artificial neural network training as input and output values. An artificial neural network, a machine learning method, consists of input, hidden, and output layers. Each layer contains artificial neurons, interconnected like neurons in the biological nervous system, forming the artificial neural network structure. A weight is assigned to the data entering the input layer and processed using an activation function, and output is acquired as a result of the calculations. This study used the hyperbolic tangent function as the activation function. In addition, functional links are used to improve the relationship between input and output. Python and MATLAB programming environments were used to develop the artificial neural network tool. As the training algorithm, the RMSProp function in the Keras library was used in the Python model, and the trainscg and learngdm functions were used in the MATLAB model. In order to minimize the differences arising from the different algorithms used by the models, the ANN structure and the data set used are the same. Accordingly, three hidden layers and 70, 90 and 40 neurons were used in these layers, respectively, in both models. In addition, the data set containing 39 input and 73 output parameters were divided into 80% training, 10% validation and 10% test set. The tools obtained at the end of the training were tested using test sets, and the error rates in the estimations of variables such as shale oil production curves, flue gas injection pressure and injection stopping time were calculated. These error rates were found to be 5.47% for the Python model and 2.54% for the MATLAB model.
Characterization of hydraulic unit and use of particle size distribution data for unconsolidated laminated sandstone formations

(Graduate School, 2024-08-09) Göral, Buse ; Kulga, İhsan Burak ; Yıldız, Hasan Özgür ; 505211503 ; Petroleum and Natural Gas Engineering

This research focuses on two important main subjects. The first study aimed to characterize the hydraulic flow unit with core data obtained from a thin, highly laminated, partially unconsolidated, shale-silty sandstone formation. The second study investigated the use of particle size distribution data obtained from the same formation but from different sources in different areas of field development. Five different measurement methods were studied in detail to perform particle size analysis. At the beginning of the thesis, which is referred to as the HU characterization phase, laboratory examinations were carried out on 77 core samples that were extracted from certain regions of the sandstone formation. The permeability and porosity data that were acquired were subsequently analyzed. In addition, two independent methods were utilized for the purpose of investigating the flow zones of the reservoir, which exhibited varied flow characteristics. The first approach utilized the Flow Zone Indicator (FZI), created by Amaefule. This methodology is popularly known as the slope approach. For a long time, people have used this well-established method to differentiate between different rock zones inside the reservoir by evaluating their flow characteristics. The method relies on hydraulic units and cumulative frequency calculations. The analysis of the log (FZI) curve involved fitting lines with different slopes to the curve and grouping points with identical slopes into the same hydraulic unit. The second method allows for a quick understanding of the flow characteristics present in distinct reservoir regions as well as a comparison of the flow characteristics present in the numerous rock sections present in different reservoirs. Guo defined a parameter known as discrete rock types (DRT), also known as the quantitative method, which makes this possible. We use the FZI values to calculate the DRT, which yields a more comprehensive result. We carried out a comparison of the required calculations and hydraulic units for both systems to identify the advantages and disadvantages of each approach. The data clearly demonstrates that Guo method is an excellent approach for determining hydraulic units. This method exhibits more responsiveness to variations in the core data, resulting in a more comprehensive examination of hydraulic units. In contrast to the first strategy, which only identified four hydraulic units, the second approach was successful in identifying a total of eight hydraulic units. In addition, the second approach provides a comprehensive hydraulic system that consists of hydraulic units with equal numbers, arranged in numerical order from the most efficient to the least efficient, under circumstances when many reservoirs display flow parameters that are comparable to one another. In the second part of the thesis, particle size estimation is used to measure particle shape anisotropy and evaluate surface area regularity. The Particle Size Distribution (PSD) classifies solid particles based on their size, revealing the proportion of each size range to the total amount of solids present. The accurate PSD of unconsolidated reservoirs is an essential variable in the field development process. PSD data is crucial for drilling fluid optimization and designing gravel pack completions. PSD data is utilized for permeability estimation when core data is not available. This research used PSD data to look into different aspects of field development for a gas-bearing, unconsolidated laminated sandstone formation within a certain unconsolidated formation. In addition to the widely used techniques for acquiring PSD data, such as sieve and laser particle size measurement, PSD data was also obtained using microscopic view, thin section imaging, and scanning electron microscopy (SEM). PSD measurements were conducted by analyzing different sources of material, depending on how the data was utilized. The primary materials collected for analysis included cores, plugs, well cuttings, debris, solids, scaling and precipitation products from well clean-up, flowback, and DST operations, as well as scaling and precipitation products from core flow tests and proppants used for gravel pack well completion. Significant variations in the PSD data were detected in the field due to its varied lithology and minerals. Precise engineering methods were employed to evaluate, compile, and utilize PSD data for the optimization of drilling fluid, the design of gravel pack completions in cased holes, and the calculation of permeability. It was determined that appropriately sized CaCO 3 might serve as an efficient bridging agent for the formation, as the formation rock with an identified PSD could assist in the formation of a high-quality filter cake. Determined the optimal proppant size and screen size needed for a cased-hole gravel pack completion based on the formation's PSD. The absence of any notable sand generation in the field confirms the effectiveness of the gravel pack assembly in avoiding sanding. A strong connection was found between the air permeability measured on cleaned and humidity-dried plugs under confining stress and the air permeability derived using various equations. It was observed that while the permeability trends were similar, there were notable differences between the measured data from the plug and the estimated data from the PSD.
Combustion kinetics of asphaltites compared to coals through isoconversional analysis

(Graduate School, 2024-07-01) Dorreh, Elahe ; Çınar, Murat ; 505211504 ; Petroleum and Natural Gas Engineering

Asphaltites are dark-colored solid petroleum, classified as a group of Bitumens based on the latest classifications; this is disputable. They are formed by alteration during or after migration, generally in oil-bearing zones. They are primarily observed in petroleum provinces. In Turkey, they are extensively observed in the southeastern and some northern parts and are commonly produced by surface mining techniques for electricity generation. On the other hand, gilsonite, a form of asphaltite produced in the US (Uinta Basin of Northeastern Utah), is used as an additive for different purposes. Asphaltites originated from conventional oil. However, they have coal-like properties, such as ash content. It would be worthwhile if kinetic signatures could be compared to coal and petroleum. In this way, a more persistent picture of asphaltite combustion characteristics is clarified. Understanding this helps to decide on information about the reaction scheme, activation energy, and general combustion behavior, and finally, the reactions probably taking place in this procedure of newly trend alternative source of energy. For this purpose, a similar set of experiments is carried out with coal, and using literature, it is compared to petroleum, respectively. This experimental work analyzes the combustion characteristics of asphaltite from the Şırnak province of Turkey through kinetic-cell experiments. Five sets of ramped temperature experiments are conducted using a 2 g asphaltite sample with different heating rates. These experiments measure the temperature inside the cell and the effluent gas composition, primarily CO, CO2, CH4, and O2 concentrations. The results indicate two O2 consumption peaks at different temperatures, corresponding to High-Temperature Oxidation (HTO) and Low-Temperature Oxidation (LTO). Before doing any analysis, some comments compared to coal and asphaltite raw data, such as the initial temperature of LTO and HTO reactions, oxygen consumption, and carbon dioxide production rates. Then, the results are analyzed using isoconversional methods. These methods require a set of experiments conducted at different heating rates and result in a so-called isoconversional fingerprint (Conversion versus activation energy). The objective of the kinetic analysis is obtaining the activation energy without assuming any kinetic model under the isoconversional assumption that the reaction rate at a constant extent of conversion is only a function of temperature. This fingerprint provides information on the reaction scheme. The same analysis was repeated using carbon monoxide and carbon dioxide production data. Carbon monoxide data does not show reliable and sufficiently accurate results. However, taking carbon dioxide data into analysis contributes significantly to figuring out the reaction scheme that might have taken place in the gasification process. Considering that asphaltites are mostly treated as coals in some regions and literature, and the procedures and processes applied to them are almost the same, it is expected to show further similarities with coals. Yet, regarding classifications, crude oil shows a closer relationship to asphaltites. Asphaltites have been proven to exhibit complex behavior regarding activation energy trends, making it hard to comment on their characteristics or reaction schemes. Therefore, a commercial simulator is used to model the gasification experiments based on coal reactions to get a better understanding. Using this commercial simulator determines the behavior of coal in the gasification process and provides a better understanding of the governing reaction. Reservoir and sample characteristics and properties, geology, reactions, heating systems, imposed heating rates, and kinetic parameters are entered as input data into the simulator. The simulation showed that carbon oxidation plays the most crucial role in the gasification process in terms of both activation energy determination and consumption rates. Furthermore, these reactions occur in the most critical phase of the gasification procedure, namely, low and high-temperature oxidations in the intermediate gasification steps. Moreover, almost all the main gasification reactions occur in the last gasification phases. Therefore, it can be concluded that the extent of the gasification of coal and asphaltite tends to behave the same in the previous phases, and the mechanisms and reactions in the final steps of asphaltite gasification are similar to coal.
Development of combustion tube experimental setup for underground coal gasification

(Graduate School, 2021) Sarıçam, İsmail Hakkı ; Çınar, Murat ; 708863 ; Petroleum and Natural Gas Engineering Programme

Traditional methods of energy production using coal are mainly based on obtaining coal by surface and underground mining. Later, the obtained coal is burned in thermal power plants and used to produce steam in steam boilers, but it is also used in homes for heating purposes. During surface and underground mining, miners work in very difficult conditions, risking their lives. Unfortunately, there have been many fatal accidents in coal mines in the past. In addition, not using enough filters in the chimneys of thermal power plants and houses, and insufficient control cause various environmental problems. The underground coal gasification process provides relatively cleaner and safer utilization of coal compared to traditional methods. The underground coal gasification process is mainly based on the production of synthesis gas (syngas) formed by gasification of the coal in situ. In the former Soviet Union, important studies were carried out, but these studies were interrupted by the cheaper production of natural gas. Significant field and laboratory work have subsequently been carried out in the United States, Europe, China, and Australia. The only operating plant on an industrial scale is the Angren underground coal gasification plant in Uzbekistan, a remnant of the former Soviet Union. After a suitable coal seam is determined for the underground coal gasification process, the production and injection well pairs are drilled into the determined coal seam. Then if it is not adequate, a connection is created between the wells to ensure gas flow between the wells. Air, oxygen-enriched air, or steam-oxygen mixture can be injected from the injection well to partially oxide coal. During the gasification of coal, several reactions take place. The drying of coal, pyrolysis and gasification processes are the main processes. First, the moisture inside the coal evaporates in the drying phase and is followed by pyrolysis. Second, with the increase in the temperature coal decomposition occurs which is also called pyrolysis. Char forms as a result of pyrolysis and char gasification take place as the final step. These processes occur simultaneously as the oxidant injection continues. As the coal gasifies, a cavity is formed in the gasification region and the cavity grows during gasification. As a result of the gasification of coal, syngas is released. Syngas mainly contains carbon dioxide, carbon monoxide, methane, and hydrogen. The released syngas is produced from the production well and transferred to the facility on the surface. Later, the produced syngas is used for various purposes as electricity generation, methanol, hydrogen, and synthetic fuel production. The underground coal gasification process depends on several different parameters, especially the coal type. Coal properties vary between coals of different ranks. Due to the complex structure of coal, it can exhibit a heterogeneous behavior even within the same seam. For these reasons, the efficiency of underground coal gasification may differ in different coal ranks and different coal fields of the same rank. The depth of the coal seam, the formation, and the geological structures around it also affect operational efficiency. In addition to the formation characteristics, the operation parameters also affect the efficiency of the underground coal gasification process. Producing a maximum amount of syngas with a high heating value by gasification of minimum coal can be described as process efficiency. Injected fluid, injection pressure, connection method between wells, and the method used for production are the operational variables that affect the efficiency of the process. Field and laboratory studies are carried out to improve the understanding of the physical and chemical properties of the underground coal gasification process and to make industrial-scale applications with the information obtained. Field studies initiated with the former Soviet Union later gained momentum in the United States. The effects of variables such as distance between injection and production wells, connection method between wells, different coal ranks, different operating pressures, and the method used for production on underground coal gasification are tried to be better understood with these field and laboratory studies. At the same time, the growth rate and geometry of the cavity that is to be formed during underground gasification are also examined in this field and laboratory studies. In this way, possible subsidences are tried to be prevented. Before initiating the pilot-scale experiments and industrial-scale operations, laboratory studies are required to determine the optimum operation parameters and coal properties. Thus; the underground coal gasification process can be accomplished in an efficient and secure way. In laboratory experiments for underground coal gasification, the coal sample can be taken as a block and block tests can be carried out. However, it is not always possible to obtain block samples. In the case of deeper seams, the samples are obtained through the well as the core. Gasification experiments can also be performed by packing the coal particles in a tube. Previous combustion tube experiments have some drawbacks in terms of their design. First, some of the previous combustion tube experiments for the UCG were executed by providing an adiabatic environment in the reactor. In these experiments, the system is designed such that heat losses are almost zero. The temperature outside the reactor tried to be equal to the temperature inside the reactor by heating the reactor from outside. While this experimental design provides fine temperature behavior throughout the experiment, it does not represent the underground conditions. There is a considerable amount of heat loss through the surrounding formations. Second, previous combustion tube experiments do not have any H2S filter. The experimental design of this study includes an H2S filter. Furthermore, heat losses were tried to minimize; however, the reactor used in this study is not adiabatic.In adiabatic operation of combustion tubes it is not clear if a self sustained combustion front is achieved since the reactor is heated externally. The provided heat could have an impact on the combustion front behavior. It is hard to differentiate the effect of external heating. In this study, a combustion tube experimental setup was developed for underground coal gasification experiments through the adaptation of combustion experiments conducted for in situ combustion of oil petroleum fıelds. Content of the syngas and the progression speed of the combustion front were followed. The amount of produced gas was not measured in this study. Dimensions of the combustion tube to be used for coal gasification experiments were determined by examining the synthesis gas content and the slopes of the temperature profiles in front of and behind the combustion zone. While determining these measurements, the situation where deviations in the composition of the syngas are small, and the slope of the temperature profile in front of and behind the combustion zone does not change was taken as a stable period. During the study, parameters such as injected fluid, coal rank, and operating pressure were also examined. One of the important factors affecting the UCG operation is the content of the injected fluid. In the literature and different field applications, gasification has been carried out using air, oxygen-enriched air, and a vapor-oxygen mixture. In a part of this study, the effect of the amount of oxygen in the injection fluid on the gasification of coal was investigated. According to the results of the experiment, it is observed that the CH4, H2, CO, and CO2 contents of the produced syngas increases with increasing oxygen content in the injected fluid. Hence, the heating value of the syngas increases with increasing oxygen content in the injected fluid. The syngas produced during the gasification of coal contains various corrosive gases, primarily H2S. The main source of released H2S is sulfur in coal. There are different techniques such as caustic scrubbing, metal oxides, and alkaline impregnated activated carbon to trap the released H2S. In this study, a caustic scrubbing column is used to mitigate H2S production. Before the syngas is released into the atmosphere, it enters this column and is purified as much as possible from the H2S. However, the H2S amount at the inlet and the outlet of the scrubber could not be measured since neither in the gas chromotagraph or the gas analyser H2S measurements are available. After the introduction of the scrubber, a substantial decrease in the rotten egg smell indicated qualitatively the decrease in the H2S concentration. In conclusion, a combustion tube experimental setup that was developed for the in-situ combustion of oil experiments was modified for the underground coal gasification experiments. The experimental setup is updated by adding an H2S scrubber and appropriate sand filters. Recommendations are provided for the common problems faced in the experiments such as clogging of the sand filter and condenser and occurrence of the second combustion front. Using a liquid trap with a longer length with a higher volume can aid the condensation of the fluid inside the gas. This can be a solution for the clogging of the sand filter and condenser since the liquid trap also acts as a condenser that keeps the excess amount of liquid. Furthermore, the effect of the O2 content of the injected fluid was also examined. It is experienced that an increase in the O2 content of the injected fluid enhances the methane, hydrogen, and carbon monoxide content of the syngas. The stable behavior can be observed for a 1 m length 7 cm diameter combustion tube with an injection rate of 6 lt/min for the lignite samples used.
Forecasting the performance of shale gas wells using machine learning

(Graduate School, 2023) Shedaiva, Mohammed ; Artun, Emre ; 824796 ; Petroleum and Natural Gas Engineering Programme

Utilization of real data to develop data-driven models in the petroleum industry has gained momentum in the past decade. The challenges related to modeling unconventional reservoirs has been recognized as the driving force behind this change in approach. Data-driven models help to enhance operations, increase efficiency and save time. In the meantime, several numerical reservoir simulators are used for modeling and forecasting the performance of shale gas wells. However, these models are computationally expensive and the simulators could indirectly face with difficulties in forecasting performance for the unconventional shale reservoirs comparing to conventional ones. This study employs a data analytics approach to investigate and gain understanding into the main driver parameters that influence the gas production performance in unconventional reservoirs (i.e. cumulative gas production after one year). The dataset utilized in this study is acquired from SPE Data Repository and consist of 53 wells (SPE, 2021). The study essentially utilized two primary methods, namely exploratory data analysis (EDA) and predictive data analytics modeling. Through the utilization of exploratory data analysis (EDA), the correlation between each reservoir and operational parameter with the cumulative gas production (Gp) is clearly identified. A number of reservoir and operational parameters display a strictly monotonic relationship with the gas production. Out of all variables, gas saturation was the variable, which demonstrated the strongest correlation. Furthermore, predictive data-analytics models based on statistical and machine learning algorithms were developed to forecast the cumulative gas production after 1 year. Among the five conducted models, extreme gradient boosting machine (XGBoost) proved to be the optimal technique for forecasting gas production, as it yielded the highest Coefficient of Determination (R2) and the lowest Root Mean Square Error (RMSE). Finally, an analysis of variable importance was conducted to determine the key variables, which have the highest predictive power in forecasting gas production performance in unconventional shale reservoirs. The operational parameters such as the number of stages, lateral length and bottom perforation along with reservoir properties such as gas saturation, porosity and thickness are more dominant than the other reservoir and operational parameters. Gas saturation is the most critical parameter, which is considered as the key driver of forecasting the gas production. The findings of this study will be beneficial in the design and development similar forecasting modelling projects.
Investigation of the inhibition characteristics of different polyamines under several temperature and shale contamination conditions in drilling fluids

(Graduate School, 2023-06-23) Çıra, Berfin ; Palabıyık, Yıldıray ; Özyurtkan, Mustafa Hakan ; 505201504 ; Petroleum and Natural Gas Engineering

Drilling fluid, which can be also called drilling mud, which is necessary to use for successful drilling, perform many functions in oil drilling, and can be composed of a mixture of many chemical additives. Drilling fluids are used in oil drilling operations for hydrostatic pressure, cutting removal from well and suspending them at static conditions, cooling lubrication of drilling equipment, and shale inhibition. Shale inhibition is an important function of oil drilling mud to provide well stability. Clay is one of the most common minerals which is found in shale formations. The smectite group (montmorillonite, also known as bentonite), which is the most common clay mineral, shows a very high swelling effect with hydration when it encounters water or water-based mud. While shales are known to make up 75% of the drilled formations, clay inhibition is a significant parameter to ensure borehole stability during drilling operations. Therefore, clay inhibitor additives are necessary, especially drilling shaly formations. In the face of the high cost, high toxicity, and adverse effects of conventional clay inhibitors on drilling mud, organic amine groups polyamines have been used as an alternative clay inhibitor in recent years in terms of their effectiveness in reducing shale hydration, low toxic effects on the environment, biodegradability, original extractions from plants, resistance to thermal stability and ability to easy expand of these properties. In the face of the high cost, high toxicity, and adverse effects of conventional clay inhibitors on drilling mud, organic amine groups polyamines have been used as an alternative clay inhibitor in recent years in terms of their effectiveness in reducing shale hydration, low toxic effects on the environment, biodegradability, original extractions from plants, resistance to thermal stability and ability to easy expand of these properties. According to these advantages of polyamines, to have an idea about their performance in deep and high temperature well conditions, studies are still being carried out on their resistance at high temperatures. So, the thermal stability of clay inhibition is a subject that is open to improvement for these polyamine additives. In this study, it is aimed to determine the clay inhibition properties of the mud samples for the increasing temperature parameter on the muds prepared with different bentonite amounts and different polyamine amounts. The study is carried out on three polyamine products with different pH values, which are coded as PA1 (pH=7.5-8.0), PA2 (pH=8.0-8.5), and PA3 (pH=9.8-10.2). To determine and compare whether these polyamine products show clay inhibition properties, CP (commercial product) shale inhibitor product is also tested as a reference product. In addition, mud samples are prepared and tested without any polyamine products, 0% polyamine case, just with fresh water and bentonite. This is necessary to see and compare the effect of the polyamine product when used. The mud samples prepared for the study are mixed under laboratory conditions, with the specified amount of bentonite, 20 g, 40 g, 60 g, and 80 g, and the determined amount of polyamine, 0%, 1%, 2%, 3%, and 4% as volume. After preparing the mud samples, they are aged in a hot roller oven for 16 hours at the specified aging temperatures, 77 °F, 150 °F, 200 °F, 250 °F, and 330 °F. After the aging procedure is done, rheological measurements, 600 RPM, 300 RPM, 200 RPM, 100 RPM, 60 RPM, 30 RPM, 6 RPM, 3 RPM dial reading, 10-second, 1-minute, and 10-minute gel strength, and capillary suction time tests are performed to observe and compare the clay hydration and swelling effect. When the results are examined, it is determined that each of the products PA1, PA2, PA3, and CP provided clay inhibition with preventing the swelling, while the product with the best clay inhibition performance is PA1. PA2 and CP polyamine products give closer shale inhibition results, and they have the second best performance after PA1. PA3 shows less clay inhibition performance compared to the other tested polyamine products, PA1, PA2, and CP. The percentage of polyamine to be used varies depending on the aging temperature and the amounts of bentonite, but the use of 2% polyamine has been found to have an optimistic use value in most cases, especially for 40 gr to 60 gr bentonite amounts. For lower bentonite amount, such as 40 g or less, 1% polyamine concentration is enough for drilling mud to provide inhibition of clay with prevent swelling. For higher bentonite amounts, such as 80 gr or more, at least 3% to 4% polyamine concentration is required to prevent clay swelling. Also, this study shows that polyamine products mostly provide thermal stability according to the increased aging temperature in terms of clay inhibition. Especially high amounts of polyamine, such as 3% to 4%, the concentration at mud creates stable shale inhibition properties against the high temperature. 2% or less polyamine concentration has also stable clay inhibition against the temperature at low bentonite amounts. Moreover, while most of polymer has bacterial degradation problems at high temperature well condition, polyamines cannot show any bacterial biodegradation at a high aging temperature, i.e., 300 °F temperature. So, polyamine does not require any biocide additive which is used in case of bacterial biodegradation. In conclusion, polyamine is an additive that has high shale inhibition against the increased bentonite. Proper polyamine amount can prevent even high bentonite amounts. Also, the polyamine is a more environmentally-friendly, efficient, and less costly shale inhibitor mud additive compared to the traditional ones.
Machine learning based selection of candidate wells for extended shut-in due to fluctuating oil price

(Graduate School, 2024-07-10) Lobut, Beyza ; Kulga, Burak ; Artun, Emre ; 505211502 ; Petroleum and Natural Gas Engineering

Fluctuations in oil prices adversely affect decision making situations in which performance forecasting must be combined with realistic price forecasts. In periods of significant drops in the prices, shutting in wells for extended durations such as 6 months or more may be considered for economic purposes. For example, prices during the early days of the Covid-19 pandemic forced operators to consider shutting in all or some of their active wells. In the case of partial shut-in, selection of candidate wells may evolve as a challenging decision problem considering the uncertainties involved. In this study, a mature oil field with a long (50+ years) production history with 170+ wells is considered. Reservoirs with similar conditions face many challenges related to economic sustainability such as frequent maintenance requirements and low production rates. It is aimed to solve this decision-making problem through unsupervised machine learning with the help of the data obtained during production. Average reservoir characteristics at well locations, well performance statistics and well locations were used as potential features that could characterize similarities and differences among wells. After a multivariate data analysis that explored correlations among parameters, clustering algorithms were used to identify groups of wells that are similar with respect to aforementioned features. Using the field's reservoir simulation model, scenarios of shutting in different groups of wells were simulated. 3 years of forecasted reservoir performance was used for economic evaluation that assumed an oil price drop to $30/bbl for 6, 12 or 18 months. Results of economic analysis were analyzed to identify which group of wells should have been shut-in by also considering the sensitivity to different price levels. It was observed that well performances can be easily characterized in the 3-cluster case as low-, medium- and high-performance wells. Analyzing the forecasting scenarios by considering "NPV per active well" and "NPV from Cash Flow" parameters showed that shutting in all low-, high- and medium-performance wells altogether during the downturns results in better economic outcomes for "NPV per active well". However, shutting in high- and medium- performance wells altogether and operating only low- performance wells during the downturns results in better economic outcomes for "NPV from Cash Flow". The results show that the "NPV from Cash Flow" parameter is most sensitive to the oil price during the high price period, while the "NPV per active well" parameter is most sensitive to the number of wells shut-in during the low oil price period. This study demonstrated the effectiveness of unsupervised machine learning in well classification, particularly for the problem studied. Operating companies may use this approach for selecting wells for extended durations of shut-in in periods of low oil prices.
New analytical model for underground storage of natural gas with carbon dioxide as cushion gas and for sequestration of carbon dioxide

(Graduate School, 2023-10-18) Gökgöz, Emel ; Türeyen, Ömer İnanç ; 505201505 ; Petroleum and Natural Gas Engineering

Natural gas is a strategically important, valuable fuel used in heating, industry and transportation. Natural gas is the smallest member of hydrocarbon paraffins. While some countries produce and export surplus natural gas, some countries are dependent on import of natural gas. Turkey is a country in need of imports for natural gas. For this reason, some of the imported natural gas is used, while the unused portion is stored for use when needed. One of the natural gas storage methods is to store natural gas underground. Depleted natural gas and oil reservoirs and salt domes can be used for underground storage. Storage of natural gas is very important for countries due to seasonally changing gas demand, fluctuations in gas prices and strategic reasons. Although the stored gas is generally methane, not all of the stored natural gas can be produced due to the pressure difference between the reservoir and the surface. Some of the stored natural gas is left in the reservoir as base gas to create pressure support. This leads to economic loss. Using carbon dioxide instead of methane as cushion gas provides significant economic, environmental, and operational benefits. In this study, the effects of using carbon dioxide as cushion gas were investigated. The physical properties of carbon dioxide and methane such as density, compressibility and compressibility factor were investigated. Although the denser of the two gases with different densities in the tank sinks to the bottom and the other one is at the top of the tank, the area between the two gases where these two gases form a homogeneous solution is called the mixing zone of these two gases. Since there will be a region consisting of a mixture of these two gases as a transition zone in a reservoir containing carbon dioxide and methane, the compressibility factor of the mixture region containing different percentages of carbon dioxide and methane was calculated using Peng Robinson Equation of State. Since looking at the physical properties, the compressibility of carbon dioxide at temperatures between 60-120 bar and 50-70 °C is higher than that of methane, it is concluded that using the same amount of carbon dioxide as cushion gas by volume gives significantly beneficial results in terms of pressure optimization and increases the amount of methane produced. Since carbon dioxide is cheaper than methane, its use as cushion gas may give satisfactory results both economically and environmentally in natural gas storage reservoirs. It is seen that the use of carbon dioxide as an enhanced gas recovery method as cushion gas in methane storage and production is more efficient in terms of reservoir management and economy. In this study, how the pressure changes during methane production in gas reservoirs containing carbon dioxide and methane as cushion gas for different production scenarios is observed by the use of the new material balance equation presented by Tureyen et al., (2023). Thermodynamically, how methane and carbon dioxide affect the reservoir properties and how they change with different initial reservoir pressures, molar percentages of methane and carbon dioxide, temperatures, and production scenarios are investigated. As a result, it has been observed that the use of carbon dioxide as cushion gas in the temperature and pressure range of 50-70 °C and 60-120 bar increases the methane storage and production efficiency, which is, the working gas capacity. Considering the compressibility behavior of methane and carbon dioxide, it has been observed that the mixing zone containing the same volumetric ratio of methane and carbon dioxide shows a compressibility factor behavior closer to methane. For this reason, a new analytical equation was introduced by taking the mixing zone into account. CO2 is injected into a reservoir containing methane initially, followingly only methane is produced from the reservoir and average reservoir pressure change is observed during the injection and production stage with analytical models where one of the analytical models does not include the mixing zone into consideration and the other one does. CMG (Computer Modelling Group) is used to verify the results. It is seen that the analytical model which includes a mixing zone gives better results than the analytical model assumes no mixing zone in the reservoir. Finally, assuming that carbon dioxide will be located in the lower part of the reservoir and methane in the upper part of the reservoir due to the density difference, it is important to observe how the transition zone of methane and carbon dioxide changes with methane production. Since only methane production is targeted, it is important to follow the transition zone height in order to prevent carbon dioxide production. For this reason, the change in the height of the transition zone between carbon dioxide and methane with methane production in the reservoir containing 50% carbon dioxide and 50% methane for different reservoir shapes such as cylindrical, trapezoidal and hemispherical was investigated.
Prediction of flow rates from different entries using PLT p-T measurements in a horizontal well by machine learning methods

(Lisansüstü Eğitim Enstitüsü, 2022-12-13) Çevik, Muharrem Hilmi ; Çınar, Murat ; 505191508 ; Petroleum and Natural Gas Engineering

Oil, which is a source of energy and raw materials, has been maintaining its importance for almost a century, and although humanity has sought alternatives, it has not been able to find a source of energy and raw materials that can replace oil and natural gas to date. The origin of the oil production process is more than a century old. Oil, which was first produced with vertical wells, can now be produced from deviated and horizontal wells with the development of technology. Today, horizontal wells have become quite common. Production logging is basically a logging method used to determine how much fluids (water, oil, gas) flow through which intervals. It is possible to measure parameters such as flow profile, pressure, temperature, ID of the well thanks to traditional production logging tools. Production logging tools, originally developed for vertical wells, have lost their function with the spread of deviated and horizontal wells. Because the flow profile in deviated and horizontal wells is quite complex compared to vertical wells. Data obtained with traditional tools are often unhealthy or incomplete data. New devices have been developed to eliminate this disadvantage. Thanks to these devices, velocity and hold-up distribution across the cross-section can be obtained. However, incomplete-inaccurate data due to mechanical problems and high costs are their disadvantages. The spread of horizontal wells allows oil and natural gas production at high flow rates. It is quite obvious that this situation is very advantageous from an economic point of view, but it also brought with it a number of technical problems. Due to the high flow rate, the pressure drop due to friction increases along the well; thus, creating an unbalanced flow profile. Eventually, water and gas coning may occur. Fortunately, ICDs (inflow control device), a product of advanced sounding technology, help solve these problems. Machine learning is the ability to learn and improve a model using data input. It provides a better understanding of the data set by making inferences from the existing data set and allows predictions to be produced using input data. Another feature of machine learning is that it is fast. It can explain analyzes that can take days in a very short time using the right model. Machine learning provides a wide range of uses that can affect many areas such as image process, classification and linear regressions. A substantial amount of data is also obtained in the oil and gas sector. This indicates that the applications of ML in the oil and gas sector will increase. In high flow wells, the roughness value becomes important as the pressure drop due to friction is high. Also, the fact that the roughness is an unknown parameter, moreover, its variation with time makes it difficult to determine. In this study, a constant flow rate interval is determined. Then, the pressure difference due to inflow-outflow and acceleration is neglected. Since the well model is created by considering the pressure difference due to gravitation, only a pressure difference due to friction is detected in this constant flow rate interval. Then, by applying the reverse solution, the relative roughness is calculated. Defining the flow profile correctly is critical for for each member of subsurface team. Although modern production logging tools are helpful in understanding the flow profile, it is prone to mechanical problems and moreover, logging with optimum conveyance requires long operation times and singinificant logging budget. Therefore, some researchers have used solely pressure and temperature data to estimate flow and determine the contribution of perforations. In addition to empirical and analytical approaches, ML applications have started to emerge recently. Considering both the rapid development of ML and its successful applications, the applicability of ML techniques to the oil and gas industry is promising. In this study, the flow rate of six production zones was estimated by using PLT pressure and temperature data obtained from two different measurements (high-choke-low-choke). The aim of this study is to produce a simple, practical and cost effective solution to the limitations of traditional Array PLT caused by mechanical problems and not working correctly in low flow regions. In this context, a well model was created and the contribution of the perforations of this model was adjusted according to the high-choke PLT (high flow) data. Various skin factors are assigned to perforations to make this adjustment. According to this model, synthetic data was produced and flow rate estimates were made for both measurements using machine learning techniques. Machine learning decision tree regression, linear regression, ridge regression and random forest regression were used for flow estimation with high-choke pressure data. 70% of the synthetic data is used for training and 30% for testing. Decision tree regression and random forest regression based on test score are the two methods that give the best results. The high-choke pressure data and the flow estimation are quite well and almost perfectly matched. Flow estimation with high-choke temperature data also gives a good result. As for flow estimation with low-choke pressure and temperature data, the test scores of both methods are above %90, but the estimates are far from low-choke flow data. However, the learning model of both ML algorithms is promising for estimating flow rate.
Prognostic reserve estimation for potential reservoirs where geochemical methods proven the hydrocarbon presence by Monte Carlo simulation: Case studies from Turkiye

(Graduate School, 2023-01-16) Aslanov, Vugar ; Palabıyık, Yıldıray ; 505181508 ; Petroleum and Natural Gas Engineering

The aim of this thesis is to calculate the prognostic reserve in areas where drilling and production have not been done before. A literature review of more than 100 wells and reservoir rocks around the world shows that the known values for the volumetric method of calculating reserves in sites with the same reservoir rock range only between two minimum and maximum values. Sometimes, even though these figures are very different from each other, they show that sites with the same reservoir rock are worth around 80%. Reservoir rocks collected from the open source literature around the world for the thesis study are divided into two separate classes as siliciclastic and carbonates. Studies show that most of the porosity, reservoir thickness and hydrocarbon saturation values collected for siliciclastic and carbonate rocks are similar values. For this reason, in this study, the same rocks (siliciclastic and carbonate) from the literature were obtained from the literature, using only potential reservoir rock types (siliciclastic and carbonate) and potential reservoir area, without using any laboratory or production data in 7 potential hydrocarbon reservoir areas in Turkey where drilling has not been done before. The underground prognostic reserve volume was calculated using computer simulation with the help of the values collected for As a result of this research, which was carried out by using Monte Carlo Simulation and a comprehensive literature review in 7 different areas in Turkey, 3 very small gas resources, 1 small gas resource and 3 super giant oil resources with 90% probability; 50% probability 1 medium, 2 small, 1 very small gas and 3 super giant oil resources; and finally, it has been determined that 1 large, 2 medium, 1 very small gas resources and 3 super giant oil resources can be found with 10% probability.
Simulation of carbon dioxide as a cushion gas in underground gas storage reservoirs

(Graduate School, 2023-10-18) Soltanov, Natig ; Türeyen, Ömer İnanç ; 505201513 ; Petroleum and Natural Gas Engineering

Fossil fuels are a part of the primary source of energy, and today the majority of industrialized and developing nations use oil, coal, and natural gas as their primary fossil fuels. Natural gas, one of these fossil fuels, is a versatile, efficient, clean-burning fuel that is utilized in a range of applications. The gas industry encompasses various sub-sectors that contribute to the overall expansion and maintenance of a reliable gas supply. One of these vital components is underground gas storage, which plays a crucial role in ensuring consistency in gas supply. Underground gas storage involves the practice of storing natural gas in reservoirs that have significant capacities. This strategic approach allows for the management of high import volumes during periods of low demand, as well as the provision of an adequate supply of natural gas during periods of high demand. The primary purpose of underground gas storage is to balance the fluctuating demand and supply dynamics of the gas market. By storing natural gas during times when demand is low, such as during the summer season or periods of reduced industrial activity, the excess supply can be stored underground in reservoirs. This practice helps to avoid the wastage of gas resources and ensures that the gas supply is readily available when demand increases. Moreover, underground gas storage facilities contribute to the overall energy security of a region or country. By maintaining a sufficient inventory of stored natural gas, countries can reduce their dependence on external sources of gas supply during times of geopolitical uncertainties or disruptions in gas imports. This enhances energy resilience and provides a buffer against potential supply disruptions, thus ensuring the uninterrupted functioning of industries, power generation facilities, and residential heating systems. Overall, underground gas storage is a critical sub-sector within the gas industry. It provides a means to balance supply and demand, manage seasonal variations, and enhance energy security. By investing in the expansion and maintenance of underground gas storage facilities, countries can increase customers' access to a reliable gas supply and strengthen their overall energy infrastructure. In the process of storing and withdrawing gas from an underground storage reservoir, certain considerations need to be addressed to ensure smooth operation. When it comes to withdrawing gas, it is crucial to maintain the average reservoir pressure above a certain value to ensure the fluent extraction of the stored gas. This is where the concept of cushion gas or base gas comes into play. The cushion gas refers to the amount of gas that needs to stay in place to maintain the required pressure levels. Traditionally, natural gas has been used as cushion gas due to its compatibility with the stored gas and the reservoir conditions. However, as alternative storage methods and gas management strategies have been explored, other gases such as carbon dioxide (CO2) have gained attention as potential cushion gases. Carbon dioxide offers several advantages as a cushion gas. Firstly, it can be readily available as a byproduct of industrial processes, making it an attractive option for utilization. Additionally, carbon dioxide can exhibit favorable thermodynamic properties, allowing it to function effectively in maintaining the reservoir pressure within the desired range. The selection and amount of the cushion gas depends on various factors, including the specific reservoir characteristics, gas storage requirements, and environmental considerations. Each gas has its own unique properties, and the choice of cushion gas should be made based on a comprehensive assessment of these factors. By employing an appropriate cushion gas, the gas storage facility can ensure that the average reservoir pressure remains above the minimum level required for efficient gas extraction. This allows for a reliable and consistent supply of gas during periods of high demand, contributing to the overall stability and effectiveness of the gas storage and retrieval process. The main objective of this study is to investigate the feasibility of utilizing carbon dioxide (CO2) as a cushion gas in an underground storage reservoir. In addition, the behavior of the mixing zone is also investigated. The simulation process is conducted using the Generalized Equation of State Model Compositional Reservoir Simulator (GEM), a software developed by the Computer Modelling Group. In this study, several scenarios are modeled using the simulation program. Each scenario represents a specific combination of reservoir conditions, including reservoir temperature, average reservoir pressure, and the compositions of carbon dioxide and methane within the reservoir. The simulation aims to provide a comprehensive understanding of how the reservoir behaves under various conditions when carbon dioxide is used as a cushion gas. By inputting the specific reservoir properties and gas compositions into the GEM simulator, the researchers can assess the performance of the reservoir in each scenario. The simulation results include data depending on factors such as reservoir pressure, reservoir temperature, and the behavior of the carbon dioxide and methane within the reservoir. These results will help to evaluate the suitability of using carbon dioxide as a cushion gas and determine the potential benefits or limitations of such a storage approach. Overall, this study contributes to the field of underground reservoir storage by investigating the use of carbon dioxide as a cushion gas, providing valuable insights into the dynamics of such a system and its potential implications for carbon dioxide storage and management strategies. Due to the different compressibility behavior of carbon dioxide at certain temperatures and pressure conditions, it can be both an advantageous and disadvantageous gas when it is used as a base gas. The results showed that carbon dioxide usage as a cushion gas at reservoir temperatures of 313.15 K, 323.15 K, 333.15 K, and 343.15 K and pressure ranges below 120 bar is quite beneficial as it provides pressure support because of its higher compressibility values than that of methane at these reservoir conditions. However, carbon dioxide loses its advantage when the initial reservoir pressure is increased to 180 bar since its compressibility is lower than the compressibility of methane at higher reservoir pressures. Moreover, the concentration of methane and carbon dioxide has a huge impact on the average reservoir pressure decline rate. Furthermore, results illustrate that the mixing zone length formed between working and cushion gas tends to extend with time. The mixing zone is assumed to be the part in which tracer concentration is between 0.1 and 0.9 and the length of the mixing zone for early, mid, and late time is 270 m, 458 m, and 567 m respectively. It was also observed that mixing zone length is proportional to the square root of dimensionless time.
Tracking pressure, hydraulic and thermal fronts in porous media

(Graduate School, 2022-01-21) Arslan, Ömer Faruk ; Türeyen, Ömer İnanç ; 505181502 ; Petroleum and Natural Gas Engineering

Geothermal energy is the heat energy stored in the subsurface. It is a clean, renewable, and sustainable energy source. Therefore, geothermal energy is a popular energy resource in the world. There are two types of utilization of geothermal energy which are direct use and indirect use. Geothermal energy is used directly for space heating, greenhouse heating, tourism, etc. However, heat energy is converted to another type of energy for indirect utilization. The main purpose of indirect utilization is electricity production. Geothermal power plants are used to convert heat energy to electricity. There are three types of geothermal power plants which are dry steam power plants, flash steam power plants, and binary power plants. For sustainable management of a geothermal resource, future performance predictions must be made. This requires good reservoir engineering practices and good reservoir characterization. One of the ways of characterizing the reservoir is by way of using tracers. Generally, tracers are made up of material that does not exist in the geothermal reservoir. Almost all of the geothermal fields in Turkey contain some amount of carbon dioxide. The carbon dioxide is usually dissolved in the geothermal water in various mass fractions. Depending on the amount, carbon dioxide can have a significant effect on production performance. Because of reinjection operations (where water with either little or no carbon dioxide is reinjected), the amount of carbon dioxide in the reservoir decreases. Depending on the reinjection amount, the produced carbon dioxide from wells also decreases once reinjected water reaches the production wells. This provides the opportunity to treat the carbon dioxide data as tracer data. Analyzing the decline of carbon dioxide at the production wells would provide a better characterization of the reservoir. Hence a model is necessary to model the decline of the carbon dioxide level. When reinjection operations are carried out, usually there are three fronts involved: the pressure front, hydraulic front, and thermal front. In this study, a model is developed to analyze how the fronts propagate in the reservoir. In the mathematical model, mass balance on the water, mass balance on carbon dioxide, and overall energy balance are applied to model pressure, temperature, and mass fraction of carbon dioxide in the geothermal reservoir. The model developed is a numerical model where the reservoir is split into grid blocks and mass and energy equations are solved simultaneously. To track pressure, thermal, and hydraulic fronts, the geothermal reservoir is divided into 175 homogenous grid blocks. These grid blocks are hydraulically connected with each other. In this study, the effects of injection operation and some petrophysical properties on the displaced pressure, thermal, and hydraulic fronts are studied. It is important to note that there are several assumptions. First, the geothermal reservoir is assumed to be a liquid dominated geothermal reservoir. Second, it is assumed that there is a 1D linear flow. Furthermore, it is important to note that injection is operated with a constant mass flow rate. Finally, the impact of carbon dioxide diffusion is ignored. Analytical equations of the breakthrough time of both thermal and hydraulic fronts are provided. Comparison of numerical and analytical solutions of these fronts are also provided.

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