Gaither Draw Unit is a heterogeneous and tight formation with an average permeability less than 0.1 mD. After more than 1.7 MMSTB water injection, there was no clear indication or benefit of the injected water from any producer. However, knowing the distribution of the injected water is critical for future well planning and quantifying the efficiency of injection. The objective of this study is to show how the Capacitance-Resistance Model (CRM) was used on this field and validated using other independent methods.
The CRM model describes the connectivity and the degree of fluid storage quantitatively between injectors and producers from production and injection rates. Rooted in material balance, signals from injectors to producers can be captured in the CRM. Using constrained nonlinear multivariable optimization techniques, the connectivity is estimated in the selected portion of the field through signal analysis on injection and production rates. In this tight formation, the whole field is divided into seven regions with one injection well and surrounding producers to conduct CRM analysis. We further use integrated but independent approaches to validate the results from CRM. The validation includes full field modeling and history match and fluid level measurement using echometering technology.
This paper focuses on a real field water flooding project in Gaither Draw Units(GDU). CRM is used to detect reservoir heterogeneity through quantifying communication between injectors and producers, and attains a production match. The fitting results of connectivity through CRM indicate permeability regional heterogeneity, which is consistent with full field modelling. The history matched full field model presents the saturation distribution showing that the majority of injected water mainly saturates the surrounding regions of injectors, and the low transmissibility slows down the pressure dissipation. Overall, the comprehensive interpretation obtained through these three independent methods is consistent, and is very useful in planning infill well drilling and future development plan for the Gaither Draw Units.
This paper shows that it is critical to integrate different sources of data in reservoir management through a field case study. The experience and observations from this asset can be applied to other tight formations being developed with water flooding projects.
In recent years, the exploration and production of oil and gas from Bakken formation in Williston Basin have proceeded quickly due to the application of multi-stage fracturing technology in horizontal wells. Knowledge of the rock elastic moduli is important for the horizontal drilling and hydraulic fracturing. Although static moduli obtained by tri-axial compression test are accurate, the procedures are cost expensive and time consuming. Therefore, developing correlation to predict static moduli from dynamic moduli, which is calculated from sonic wave velocities, is meaningful in cutting cost and it makes the unconventional oil and gas exploration and production more efficient.
Literature review indicates such a correlation is not available for Bakken formation. This may be attributed to the extremely low success rate in Bakken core sample preparation and not enough published data to develop correlation to relate dynamic moduli to static moduli. This study measures and compares the moduli obtained from sonic wave velocity tests with deformation tests (tri-axial compression tests) for the samples taken from Bakken formation of Williston Basin, North Dakota, USA. The results show that the dynamic moduli of Bakken samples are considerably different from the static moduli measured by tri-axial compression tests. Correlations are developed based on the static and dynamic moduli of 117 Bakken core samples. The cores used in this study were taken from the core areas of Bakken formation in Williston Basin. Therefore, they are representatives of the Bakken reservoir rock. These correlations can be used to evaluate the uncertainty of Bakken formation elastic moduli estimated from the seismic and/or well log data and adjust to static moduli at a lower cost comparing with conducting static tests. The correlations are crucial to understand the rock geomechanical properties and forecast reservoir performance when no core sample is available for direct measurement of static moduli.
Flow pattern of a multi-phase flow refers to the spatial distribution of the phase along transport conduit when liquid and gas flow simultaneously. The determination of flow patterns is a fundamental problem in two-phase flow analysis, and an accurate model for gas-liquid flow pattern prediction is critical for any multiphase flow characterization as the model is used in many applications in petroleum engineering. The objective of this study is to present a new model based on machine learning techniques and more than 8000 laboratory multi-phase flow tests.
The flow pattern is affected by fluid properties, in-situ flow rates of liquid and gas, and flow conduit geometry and mechanical properties. Laboratory data since 1950s have been collected and more than 8000 data points had been obtained. However, the actual flow conditions are significantly different with any laboratory settings. Therefore, several dimensionless variables are derived to characterize these data points first. Then machine learning techniques were applied on these dimensionless variables to develop the flow pattern prediction models. Applying hydraulic fundamentals and dimensional analysis, we developed dimensionless numbers to reduce number of freedom dimensions. These dimensionless variables are easy to use for upscaling and have physical meanings. We converted the collected data from actual laboratory measurement to the variations of these dimensionless variables. Machine learning techniques on the dimensionless variable significantly improved their predictive accuracy. Currently the best matching on these laboratory data was about 80% using the most recently developed semi-analytical models. Using machine learning techniques, we improved the matching quality to more than 90% on the experimental data.
This paper applies machine learning techniques on flow pattern prediction, which has tremendous practical usages and scientific merits. The developed model is better than current existing semi-analytical or classical correlations in matching the laboratory database.
The supersonic separation is a new approach to dehydrate the natural gas in recent years. In the conventional structure, the straight tube is typically combined with a cyclone to create a strong vortex flow. The shock wave usually occurs near the swirling device in the supersonic separator, which can make the flow unstable and decrease the separation efficiency. Due to removing the negative effects of the shockwave, a newtype helical guide blade is designed as the swirling device, installed in the separate straight tube in the supersonic cyclone separator. The flow characteristics in the supersonic separator was investigated and the geometry structure was optimized by performing the computational fluid dynamics modeling methods. The optimization results showed that the model with a converging tube of 190 mm length, a diverging tube of half-cone angle of 5 and a single blade installed in the middle position, is the best supersonic separator model in the dehydration process, which can create the most stable flow field and achieve the optimum separation. In addition, when the outlet back pressure in the diffuser tube is 1 Mpa 1.5 Mpa, the separation performance will be better.
Han, Guoqing (China University of Petroleum) | Ma, Gaoqiang (China University of Petroleum) | Ling, Kegang (University of North Dakota) | Gao, Yue (Sinopec Research Institute of Safety Engineering) | Zhang, HE
Nowadays, unloading gas wells with coiled tubing is a common application to the field. However, there is still lack of adequate understanding of dynamic behavior of the unloading process. Especially, there is no mature dynamic simulator for this unloading process in China. Therefore, it is necessary to study the dynamic process of liquid unloading with coiled tubing for parameter analysis and optimization. This paper studies dynamic process of liquid unloading by gas lift with coiled tubing. This unloading process includes three stages: liquid rising in tubing, liquid slug production, and liquid production by entrainment. In each stage, the mass and linear momentum conversation equations are applied to each component of the system. The components of each stage includes coiled tubing, coiled tubing-tubing annulus, liquid slug, gas bubble, and liquid film. And empirical correlations used in model include surface gas injection choke, check valve, friction factor, the relationship between the gas bubble and the liquid slug velocity, inflow performance relationship, and fluid properties. From the above, the dynamic model couples real-time change of inflow performance relationship with tubing performance. The LU factorization and the Euler method are used to derive the dynamic model, and program the dynamic model with the Visual Basic language to calculate and analyze all the variables describing a whole dynamic process as functions of time. Among all these variables, the most important ones include gas injection rates, pressures at various locations, positions of the liquid slug and gas bubble, and various velocities. Based on the dynamic model, the dynamic simulation of liquid unloading process is achieved, and the basis for design optimization of parameters is provided.
Sucker rod pumps provide mechanical energy to lift oil from bottom hole to surface when oil wells do not have enough energy to produce the oil through natural flow. It is efficient, simple, easy to be operated, and can be applied to slim holes, multiple completions, and high-temperature and viscous oils. The disadvantages include excessive friction in crooked holes, solid-sensitive problems, low efficiency in gassy wells, limited depth, and bulky volume. The load on the rod is one of the key factors that dictate the maintenance frequency of pumping unit, energy consumed to lift the fluid, and the optimization of pumping system operating parameters.
The cyclic load applied on the rod causes the fatigue and finally the failure of the rod if not designed properly. The rod load is a function of friction force, plunger acceleration/deceleration, weights of plunger, fluid being lifted, and sucker rods string, and the pressures above and below on plunger. Literature review indicates that a model to accurately calculate the load of a pumping cycle is highly desired. In this study, we couple the wellbore with reservoir performance to better analyze the dynamics of pump system, which yields more accurate results.
In this study, force balance during the pumping cycle is analyzed. Friction force due to the movement of the plunger and the rod, buoyant force, and gravity force are included in the modeling. The effects of acceleration and deceleration of the plunger on rod are considered. The sensitivity of pumping speed is investigated. This study proposed a more general model comparing with former researches because more factors that affect the load applying on rod are included. Including the friction force due to the viscous fluid is critical to rod load analysis in pumping heavy oil.
The proposed model is significant to the cyclic fatigue and failure analysis of rod in sucker rod pumping system. It can be used to predict the possible failure point for rod string by analyzing load along the whole string. It is also a useful tool to design the tapered rod string to minimize the maximum rod load while achieving optimum rod string life. Therefore, an optimization of sucker rod pumping system is implemented by balancing the tradeoff between the maximum rod string life (or rod size) and the minimum rod load (or lowest energy consumption).
Zhong, Xun (Department of Petroleum Engineering, University of North Dakota) | Wang, Yuhe (Department of Petroleum Engineering, Texas A&M University at Qatar) | Pu, Hui (Department of Petroleum Engineering, University of North Dakota) | Li, Wei (College of Petroleum Engineering, Northeast Petroleum University) | Yin, Shize (Missouri University of Science and Technology) | Ling, Kegang (Department of Petroleum Engineering, University of North Dakota)
Chemical enhanced oil recovery(EOR) such as polymer flooding and alkali/surfactant/polymer(ASP) flooding have been applied throughout the world for more than several decades. However, few large-scale successes of these technologies have been reported, except in China. The annual crude oil production rate by chemical EOR in Daqing Oilfield has been kept over 10.0 million tonnes (~73.5 million barrels) per year for 16 consecutive years. Considerable experience has gained and lessons have learned on large-scale chemical flooding, including major factors that influence the recovery factor and methods to increase the oil recovery; measures to obtain the highest economic efficiency; and how to minimize the costs.
To date, incremental oil recovered by polymer flooding is over 10.0% OOIP. Due to some disadvantages of polymer flooding, like the existence of inaccessible pore volume and lack of the EOR mechanism of ultralow interfacial tension, some substitute technologies are needed, and ASP flooding is a promising one, which was reported and proved to have an ability of recovering more than 20.0% extra oil over water flooding. However, negative scaling problems caused by alkali are severe and problematic, as a result, weak-alkali ASP (WASP) and even surfactant-polymer (SP) flooding were developed or are under development. To alleviate the bad effets of scale and further improve the performance of ASP flooding, some new technologies such as refracturing and application of new anti-scaling chemicals like compound scale removal agent were applied. SP flooding is a theoretically feasible EOR technology, but there are few field test data available, and more effective surfactants are required.
In this paper, the development of commonly used chemical flooding technologies, normal problems that may merge during commercial implementation, together with the updated solutions are included. All the valuable experience obtained from commercial-scale application of chemical flooding in Daqing Oilfield is not only of great significance for the expansion of Daqing Oilfield itself, but also worth learning by other countries.
Geological carbon sequestration represents a long-term storage of CO2, in which large-scale CO2 is injected into the subsurface geologic formations, such as the deep saline aquifers or depleted oil and gas reservoir. In the CO2 sequestration process, the injected CO2 is expected to remain in the reservoir and not to migrate to the earth surface. To better understand the CO2 movement undersurface and obtain real time information in carbon sequestration, an iridium oxide-based Severinghaus-type CO2 chemical sensor was constructed and tested in this study.
The CO2 sensor was designed and constructed based on the intersection inspiration from electrochemistry idea. The principle of the CO2 sensor design is dramatically rely on the pH detection of the electrolyte solution which generated by the hydrolysis process of CO2. The developed CO2 sensor includes a couple of Iridium-Oxide electrodes. To meet the working purpose, iridium oxide nanoparticles was prepared and electrodeposited for the thin IrO2 film generation on the surface of metal substrate. The other critical parts, such as a thin gas-permeable silicone membrane, a porous metal supporting material, and the bicarbonate-based electrolyte solution are prepared for the sensor’s preparation. The assembled sensor was tested in aqueous solution with different CO2 concentrations. Then the sensor was settled in harsh, high-pressure environments, in order to invest the performance of the CO2 sensor under reservoir conditions.
The definition of CO2 sequestration was the whole process of the CO2 capture and the CO2 long-term storage . It had been treated as a potential method to decelerate the accumulation process of greenhouse gas which generated from the fossil fuels burning and other source . While for the geologic sequestration, it means to put the captured CO2 in the geological formation for the aim of long-term storage.
Because of its efficiency, cleanliness, and reliability, natural gas is an important sector in global energy consumption. It supplies nearly one-fourth of all energy used in the United States and is expected to increase 50% within the next 20 years. More gas-delivery infrastructure is being constructed to meet the transportation requirement of the ever-increasing demand for natural gas, while at the same time, the existing gas infrastructure is aging. Ensuring natural-gas-infrastructure reliability is one of the critical needs for the energy sector. Operators prefer to capitalize on the transportation capacity of these old pipeline systems to reduce the cost for building new pipelines, but they run a high risk of encountering partial blockage in the pipeline, which can cause operating pressure to exceed the safety specification. Therefore, the reliable and timely detection of a partial blockage in a gas pipeline is critical to ensuring the reliability of the natural-gas infrastructure.
To design proper pigging tools, it is important to detect the location and size of partial blockages. Physical inspection and mathematical-model simulation are used to identify partial blockage in gas pipelines. Generally, the physical method can result in an accurate detection of the location and size of the partial blockage, but at the expense of production shutdown and high cost/long time to run the physical detection, which is a very expensive measure in a long-distance gas pipeline. The mathematical simulation detects partial blockage through numerical modeling, which could provide a quick evaluation at a much lower cost, but with higher uncertainties. Our literature review indicates that a simple, practical, and reliable method to detect partial blockage without a recorded inlet or outlet pressure is in great demand.
In this study, we develop a multirate test method to detect partial blockage in a gas pipeline. By conducting multirate tests, the location and size of the partial blockage can be evaluated. The new method can be applied under the conditions of no measured inlet or outlet pressure, which have not been investigated before. It is worth locating a partial blockage under these conditions because as oil and gas exploration and production move to harsh environments, no pressure gauge being installed at the inlet or outlet of the pipeline can be a common circumstance in the fields. Even for onshore fields or fields with easy access, pressure is not transferred to the central office in real time. In addition, the metering equipment and pressure gauges installed in the pipeline may not be working. Therefore, our method provides a practical, quick, and low-computational-cost approach to estimate partial blockages corresponding to these conditions.
The partial blockages in a single pipeline and in parallel/looped pipelines were evaluated in this project by use of the proposed method. Considering that most of the complicated pipeline systems under operation can be decomposed into basic units, such as single pipeline and parallel/looped pipelines, the proposed model can realistically and feasibly identify partial blockage in a complex pipeline network. Furthermore, existing studies assume only single partial blockage in the pipeline, which limits the application of available models because the detection will be misleading if there is more than one partial blockage in the pipeline. To fill this gap, we developed a model to differentiate the single-partial-blockage scenario from the multiple-partial-blockage scenario on the basis of multirate tests. The identification is critical because it guides partial-blockage detection in the right direction.
Han, Guoqing (China University of Petroleum) | Pan, Zhejun (CSIRO Energy) | Zhang, He (University of North Dakota) | Ling, Kegang (University of North Dakota) | Teodoriu, Catalin (University of Oklahoma)
In Coalbed Methane (CBM) reservoir, especially the thin low permeability CBM reservoirs, undulating horizontal wells are often drilled to maximize contact area with the reservoir for higher CBM production rates. Coal fines, however, may accumulate in the wellbore, making pressure along the wellbore trajectory more complex, affecting gas production behavior. This paper presents experimental work to study the coal fines-water-gas three-phase flow in transparent pipes to mimic different undulation angles that may occur in horizontal wells. Coal fines with different particle sizes are studied. Observed from the experiments, four flow patterns for coal fines migration were identified: stratification, saltation, moving dunes, and dispersed flow. Moreover, relations between coal fines critical moving velocity and discharge velocity and the size of coal fines are investigated. This paper further investigated the settlement and plugging of coal fines at the curvature section of the pipes under four flow regimes: elongated bubble, transition, slug, and intermittent flows. Using the experimental data, we estimated the boundaries for five flow regimes under five different undulation angles. The analyses indicated that the pressure fluctuation magnitude increases when flow regime evolves from bubble flow to intermittent flow. The largest pressure fluctuation and the lowest fluctuation frequency take place under intermittent flow. Based on the experimental data, this paper derived the critical velocity correlation for coal fines in undulating CBM wellbore. The findings of this study is useful for CBM development in the field, which may help to optimize wellbore geometry to minimize coal fine settlement/plugging, act as a guide in designing well flushing operation to effectively circulate coal fines out of bottomhole.