In this work, we show a case study of using fire flooding process in thin interbeded heavy oil reservoirs to tackle the problems of low oil production rate, low gas oil ratio, and low oil recovery factor in later stage of cyclic steam stimulation (CSS) operations. The fire flooding process was adopted for the Block D reservoir in Liaohe Oilfield, China.
The depth of Block D heavy oil reservoir is 800-1200m. The reservoir includes 30-40 thin layers in vertical direction, with average thickness of 2.2m per layer. Through laboratory experiments, numerical simulation, and analysis of surveillance data from the initial small scale field pilot, we improve the understanding of fire flooding recovery mechanisms in thin interbeded reservoirs. Then, technical limits such as reservoir thickness, number of layers and permeability contrast are established for successfully conducting fire flooding with high temperature oxidation. Reaction types identification methods based on corresponding field surveillance data are also proposed. Using such guideline, we have deployed fire flooding expansions in Block D reservoir with more well patterns.
It has been proven that fire flooding process with the designed well patterns can improve recovery and sweep, and make the wells more productive with enhanced inflow from multiple directions. The process technical limits successfully guides us in properly expanding the project. Reaction type identification method further helps to perform continuous dynamic surveillance of the high/low temperature oxidation burning state of the combustion front in the field. The initial pilot test includes 7 well patterns, which have been operational since 2005. Up to now, we have deployed a total of 105 fire flooding well patterns in Block D reservoir. Within the fire flooding area, the single-well oil production rate has doubled on average, with the reservoir pressure also doubled. For the multi-layered block D reservoir, the ultimate oil recovery factor for fire flooding can reach up to 55%, an increase of 28% from the expected recovery of CSS.
In conclusion, we have shown in this work that fire flooding process can be applied to deep thin to medium thickness interbeded heavy oil reservoirs. As a follow-up process in later stage of cyclic steam stimulation, it can significantly increase oil recovery and process performance.
Kholy, S. M. (Advantek Waste Management Services) | Sameh, O. (Advantek Waste Management Services) | Mounir, N. (Advantek Waste Management Services) | Shams, M. (Advantek Waste Management Services) | Mohamed, I. M. (Advantek Waste Management Services) | Abou-Sayed, A. (Advantek Waste Management Services) | Abou-Sayed, O. (Advantek Waste Management Services)
Oilfields produce huge amount of waste on daily basis such as drilling mud, tank bottoms, completion fluids, well treatment chemicals, dirty water and produced saltwater. These waste types represent a real challenge to the surrounding environment especially when the oilfield is located within a sensitive environment as in the Western Desert where there are natural reserves and fresh water aquifers. Waste slurry injection has proven to be an economic, environmentally friendly technique to achieve zero waste discharge on the surface over the past years. This technique involves creating a hydraulic fracture in a deep, subsurface, non-hydrocarbon bearing formation which acts as a storage domain to the injected slurrified waste. The objective of this study is to evaluate the feasibility of waste slurry injection in an oil prospect located in the Western Desert. The evaluation includes assessing the subsurface geology, recognizing the possible candidate injection formation(s), and designing the optimum injection parameters.
Both geological and petrophysical data have been used to create the geomechanical earth model for an oil prospect located at Farafra oasis in the Western Desert. This model defines the mechanical properties, pore pressure, and in-situ stresses of the different subsurface formations. Afterwards, a fully 3D fracture simulator has been used to simulate the fracture growth within the candidate injection zone at different injection scenarios. Additionally, the fracture simulator has assessed the containment of the created fracture within the candidate injection formation(s) due to the presence of stress barriers above and below the formation. Finally, the formation disposal capacity has been calculated for each of the injection scenarios using a stress increment model.
The geomechanical earth model shows that there is a good candidate injection zone which is upper/lower bounded by stress barriers. More importantly, it is located deeper than the local fresh water aquifer and thus no contamination is expected to the fresh ground water. In addition, the possible candidate is not a hydrocarbon bearing formation.
A 3D fracture simulator has been used to determine the optimum injection parameters such as: the injection flow rate, the volumetric solids concentration, the slurry rheology and the injection batch duration. These optimum parameters are defined to minimize the stress increment rate over the well life, which ensure the highest disposal capacity and to contain the fracture within the candidate injection formation.
Guidelines to conduct waste slurry injection technique in a new oil prospect that is located within a sensitive environment as in the Western desert are presented in this study. Also, the study highlights that this technique is economic for disposal of the different oilfield waste types in an environmentally friendly fashion.
Magana-Mora, Arturo (Drilling Technology Team, EXPEC ARC, Saudi Aramco) | Gharbi, Salem (Drilling Technology Team, EXPEC ARC, Saudi Aramco) | Alshaikh, Abrar (Drilling Technology Team, EXPEC ARC, Saudi Aramco) | Al-Yami, Abdullah (Drilling Technology Team, EXPEC ARC, Saudi Aramco)
Thorough preplanning and best drilling practices are effective in reducing stuck pipe incidents, data analytics offer additional insight into further reducing the significant non-productive time (NTP) that results from this unplanned event. The severity of the stuck pipe problem may stop the drilling operations for a short time, or in more difficult cases, the drill string has to be cut and the borehole is sidetracked or plugged and abandoned. Consequently, detecting the early signs of this problem, in order to take the right actions, may considerably or entirely reduce the risk of a stuck pipe.
Although computational models have been proposed for the early detection of the stuck pipe incidents, the models are derived from a reduced set of wells with stuck pipe incidents, which may result in under-trained models that predict a large number of false positive alarms. A sufficient amount of data or wells that statistically represent the parameters surrounding stuck pipe incidents under different circumstances is required in order to derive a generalizable and accurate prediction model. For this, we first derived a framework to automatically and systematically extract relevant data from the historical data. As such, our framework searches through the historical data and localizes the surface drilling and rheology parameters surrounding the stuck pipe incidents. Moreover, we performed feature selection by selecting the top-ranked parameters from the analysis of variance, which measures the capability of the drilling and rheology parameters to discriminate between stuck pipe incidents and normal drilling conditions, such as, weight on bit, revolutions per minute, among others.
Using the relevant features selected by the analysis of variance, we derived a robust and fast classification model based on random forests that is able to accurately detect stuck pipe incidents. The implemented framework, which includes the automated data extraction module, the analysis of variance for feature selection, and prediction, is designed to be implemented in the real-time drilling portal as an aid to the drilling engineers and the rig crew in order to minimize or avoid the NTP due to a stuck pipe.
This paper is dedicated to enhancing Organizational Health and Adaptability by finding a suitable leadership model for service companies in the oil & gas industry in the Arabian Gulf. This becomes a more challenging task if you are dealing with multicultural teams.
The author relied on literature review to define the variables that can be correlated with or impact the choice of leadership styles. Variables such as the culture of the team, the characteristics of the leader, Industrial or occupational constraints. All these variables were considered & studied. A field research was also conducted to stand on the views of both the field personnel & management and test their perceptions regarding the subject matter.
A quantitative approach relied on a questionnaire that was used as the base for testing field team's perception. And a qualitative approach relied on one to one interviews with members in management in leading positions to stand on the applicability of leadership models and the constraints involved. Three main leadership models were tested.
This research paper is believed to add value to the body of knowledge as it focuses on a specific sector of a specific industry in a specific region and guides its leaders towards being more effective in their roles in order to achieve better results.
We present a software framework tailored to seismic applications embedding high performance features. Especially, we discuss the spatial cache-blocking algorithm for the Finite-Difference Time-Domain (FDTD) method and the protocol to find optimal parameters. We apply our modeling engine to perform 3D elastic seismic modeling on a large-scale 877 km2 land survey. The velocity and density models are built with geological stratigraphic forward modeling. In total, 162300 shot gathers are computed with a maximum frequency of 20Hz and a maximum offset of 5 km. The main trait of the computed data is the complexity related to the surface-waves, especially their long and dispersive wave-train obscuring other wave arrivals. Computations were performed on the Kaust supercomputer Shaheen II. The modeling campaign took one month to complete using in average 2434 compute nodes in parallel. This achievement represents a workload of 59.6 ExaFLOP on a current PetaFLOP/s machine. This indicates that the next generation of supercomputers targeting the ExaFLOP/s sustained performance, would allow reducing the run-time of our application to one hour or less. With such performance, it is reasonable to predict that 3D elastic imaging will be a routinely used algorithm by seismic exploration in the years to come, while nowadays it still requires leading-edge hardware.
Mi, Lidong (Sinopec Petroleum Exploration and Production Research Institute) | Hu, Xiangyang (Sinopec Petroleum Exploration and Production Research Institute) | Jia, Ying (Sinopec Petroleum Exploration and Production Research Institute) | Liu, Qianjun (China University of Petroleum)
Multilayer commingled production is a common means for the development of multilayer tight gas reservoirs. The understanding of the production from each formation plays a significant role in the fine description of reservoir and remaining gas distribution, especially for the water-producing gas wells. In this paper, a dynamic method for production splitting of water-producing gas wells is introduced. First, a dynamic permeability calculation method is established based on the relative permeability curve and the water-gas ratio. Then, based on the catastrophe theory, a dynamic production splitting method considering the influence of various factors (reservoir characteristics, development characteristics and geological characteristics) is established. Finally, a dynamic production splitting system is developed of multi-layer combined production gas wells. The verification of production test data shows that the dynamic splitting method can better fit the production test results and accord with the actual production situation. This novel method can be used to split the production for the multilayer combined production well.
Additive Manufacturing (AM) is a set of technologies that has historically found fertile applications in the aerospace and healthcare industries, while adoption in the oil and gas (O&G) sector has progressed slowly. Nonetheless, AM is reaching maturity in this industry as well, allowing for significant innovation. This paper describes how AM has been integrated within the value chain of a major oilfield supplier, highlighting specific peculiarities for each of its business segments. "Fullstream" activities of the oilfield supplier cover the entire O&G value chain, from the exploration of reservoirs and production (upstream) to the transportation and storage of hydrocarbons (midstream), as well as refining and industrial power processing (downstream). AM technologies in this company were originally deployed for rapid prototyping, but they have matured as strategic manufacturing pillars to address the maintenance of equipment of all industry segments within the company. Several manufacturing methods within the AM landscape can be deployed, depending on the technical requirements of the components and the environment in which they operate. O&G equipment end users face several challenges when dealing with spare parts management, such as performance, total cost of ownership, procurement time, inventory levels and obsolescence. From an OEM standpoint, serving a wide fleet with a variety of products and their different versions (with an unpredictable and unstable demand) is challenging. AM is the tool that enables a new way to serve such an installed fleet. The company has already experimented with several applications regarding obsolete spare parts re-introduction through AM, gaining strong benefits (50% +) in terms of cost and procurement time reduction. Consequently, it is important to continue adopting AM to deliver faster outcomes for the customer at first. This, in turn, fosters the development of sound knowledge and references that can then be used to develop further solutions and value propositions for the customers.
Supercharged pressures exist when drilling fluid losses (spurt, dynamic and static) invade the near well-bore region and creates a ‘supercharged’ pressure zone that is higher than the reservoir pressure but lower than the wellbore hydrostatic pressure. Due to the overbalanced hydrostatic pressure the fluid invades but cannot be disbursed because of the low mobility of the rock. This creates a near well-bore region with pore pressures between hydrostatic (wellbore) and reservoir pressure. This typically occurs in low mobility formations where the dispersion of the invaded drilling fluids is not efficient. Determining true reservoir pore pressure in these conditions is difficult for formation pressure testing tools (FPT's) which measure elevated pressures above true reservoir pressure in these conditions. Analyzing the change in measured pressures from repeated tests using FPT's may help estimate the true formation pressure.
One characteristic indication of supercharging is successive pressure build-up tests (after small drawdown volumes) that stabilize at lower pressures with each subsequent test as more supercharging fluid is removed from the near well-bore region. The successive decrease in build-up pressure as a function of volume can provide information on the dynamic pressure environment in the near wellbore zone and the reservoir pressures further from the wellbore. Plotting the pressure drop as a function of fluid volume removed from the formation and fitting an exponential decay curve to the data provides an estimate of the reservoir pressure. The curve is optimized using a regression algorithm to find a best match. Because one of the unknown variables is the desired formation pressure, a range of formation pressures are evaluated and a χ-squared error function is minimized, thus approximating the true reservoir pressure.
Numerical simulation models with known formation pressures were set-up with a static supercharged near well-bore environment and various pressure tests were conducted. Analysis was performed on a number of tests to optimize the regression algorithm. The optimized regression provided an indication of the reservoir pressure within 2% of the simulated value. Real data examples were also analyzed with good results.
This analysis technique provides a novel empirical method for estimating reservoir pressures in supercharged environments by investigating the change in build-up pressures in successive tests. The analysis can be accomplished with pressure measurement data from standard FPT's. Furthermore, the individual pressure tests do not need to stabilize because the change in pressure is used nor do the pressure tests need to measure the true reservoir pressure because it is determined by a regression analysis.
Data telemetered in harsh environments are traditionally compressed, filtered, and processed before being transmitted, if telemetered at all. The user then has limited information about the status of monitored systems; however, the user's knowledge can be improved by real-time raw information transmission.
In harsh environments, data are traditionally transmitted over dedicated lines, through variations in a power source, or wirelessly. These methods suffer from signal attenuation and dispersion over long lengths, leading to lower data rates. Optical fiber systems, however, have low attenuation, little dispersion, and can use a variety of communication schemes, such as varying signal amplitudes, phases, or wavelengths. In particular, quadrature amplitude modulation (QAM) or pulse amplitude modulation (PAM) methods common for fiber telemetry backhauls can achieve greater bandwidths in harsh environments to realize real-time data retrieval without the need for processing.
This paper reviews the current state-of-the-art fiber-optic telemetry systems for harsh environments and discusses a proof-of-principle demonstration using higher-order optical modulation techniques to obtain data rates that are orders of magnitude greater than those achieved by electrical telemetry equivalent systems. The demonstration consisted of optical and electrical components that operated at temperatures up to 200°C and transmitted data along 18 km of fiber with over 10 dB of optical margin. The current state of the project and its application to a wide variety of possible field uses are explored.
Additionally, the use of fiber communications is reviewed to help improve data delivery to users in the energy industry, a topic of growing interest. It also highlights the innovative approaches for developing real-time, high-data-rate, bidirectional optical fiber telemetry for harsh environments.
Surfactants have been used in the oil industry for decades as multi-functions additive in stimulation fluids. In hydraulic fracturing, surfactants and microemulsions have been extensively reported numerously as flowback additives to lower surface and interfacial tension to aid water recovery. Fracturing fluids invade the matrix during the fracturing, and if not recovered, leads to water blockage and a reduction to relative permeability to gas or oil. This problem is more challenging in low- permeability formations since capillary forces have more profound impact on water retention, and hence water recovery and subsequent oil productivity.
In this work, surface tension, interfacial tension, foam stability, sand-packed columns, and coreflood experiments were performed on a selected environmentally friendly water-based surfactant formulation. The performance of the surfactant of interest was compared to two commercial microemulsion and one non-ionic alcohol ethoxylated.
The results confirmed the benefit of using surfactants for flowback compared to non-surfactant case. Surface tension (ST) alone cannot be used as a selecting criterion for flow back. The alcohol exthoxylated, while reducing the ST to same level as the two microemulsions, showed very poor performance in packed column and coreflood tests. Although interfacial tension (IFT) seems to be more reasonable criteria, adsorption and emulsion tendency are other challenges that can hinder the performance of good surfactants with low IFT. Based on the data, a surfactant that lowers the IFT with the selected oil to below 1 mN/m is more likely to outperform other surfactants with higher IFT.