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Abstract Basin-wide heterogeneity of production in unconventional resources creates additional risk in field development planning. In the past few years, several data-driven models have been developed to increase the accuracy in predicting the recovery from shale gas and tight oil wells. However, many of the machine learning methods with so called "black box" approach provide deterministic results. Therefore, understanding the uncertainty associated with different development scenarios would be difficult to obtain. We have investigated the underlying statistical distribution functions that govern the production rates and decline behavior of unconventional wells. Identification and quantification of these distribution functions provide a strong tool to accurately forecast the cumulative production of a large group of wells in an unconventional basin. By understanding the relationship among geologic characteristics of different sections of the asset, and the impact of varying drilling and completion parameters, capital allocation can be done in a more efficient manner. In this paper, we have identified the statistical distribution parameters of decline behavior is a Power Law model. In doing so, we have used unsupervised clustering techniques to find an optimal number of clusters that enable observing well behaved and identifiable underlying distribution functions. Furthermore, we quantified different types of distribution functions in a trial and error workflow to provide a tool for accurately evaluating the impact of varying geologic parameters on the decline behavior of these wells. Our results show that the leading term (or leading coefficient), which also highly correlates with long term cumulative recovery, demonstrates Gamma distribution, while the power degree (or power coefficient) demonstrate Normal distribution. Peak production rate (maximum average daily rate), terminal rate (rate after switch point), and the time of terminal rate occurrence, all demonstrate Log Normal distribution.
Abstract Most waterfloods in California target sandstone formations that are unconsolidated in nature with high porosities and high permeabilities. These formations are also characterized by high Poisson ratios and low values of Young's Moduli. There has been a concern if, during the waterfloods of these types of formations, fracturing takes place at high-injection gradients. The influence of various factors on leak-off is studied in detail, indicating that with an increase in rock permeability, the leak-off velocity increases. This study included a comprehensive analysis of the characteristics of such soft formations and their responses to high injection gradients. We show that if the leak-off factors are adjusted to reflect high permeability and proper geomechanical properties, the probability of fracture formation is nil at injection gradients up to 0.9 psi/ft, for unconsolidated rooks. We computed estimated fracture width, fracture height, fracture length and noted for all three calculations, it takes gradients approaching 1psi/ft to note a non-trivial estimated value for these characteristics. This study shows that for unconsolidated formations like those in California targeted for waterfloods, the probability of fracture formation under pressure gradients of 0.9 psi/ft. is nil, and high injectivities can be exercised without the fear of fracture formation.
Abstract The rate of penetration (ROP) was optimized using a particle swarm optimization algorithm for real-time field data to reduce drilling time and increase efficiency. ROP is directly related to drilling costs and is a major factor in determining mechanical specific energy, which is often used to quantify drilling efficiency. Optimization of ROP can therefore help cut down costs associated with drilling. ROP values were chosen from real-time field data, accounting for weight on bit, bit rotation, flow rate variation along with bit wear. A random forest regressor was used to find correlations between the dependent parameters. The parameters were then optimized for the given constraints to find the optimal solution space. The boundary constraints for the ROP function were determined from the real-time data. The function parameters were optimized using a particle swarm optimization algorithm. This is a meta-heuristic model used to optimize an objective function for its maximum or minimum within given constraints. The optimization method makes use of a population of solution particles which act as the particle swarm. These particles move collectively in the given solution space controlled by a mathematical model based on their position and velocity. This model makes use of the best-known solution for each particle and the global best position of the system to guide the swarm towards the optimal solution. The function was optimized for each well, providing optimal ROP values during real-time drilling. A fast drilling optimizer is crucial to automate and streamline the drilling process. This simultaneous optimization of ROP based on real-time data can be implemented during the process thereby increasing the efficiency of drilling as well as reducing the required drilling time.
Javaheri, Mohammad (Chevron) | Tran, Minh (University of Southern California) | Buell, Richard Scot (Chevron) | Gorham, Timothy Lee (Chevron) | Sims, Jack (Chevron) | Rivas, Stephen (Chevron) | Munoz, Juan David (Chevron)
Abstract Horizontal steam injectors can improve the efficiency of thermal operations relative to vertical injectors. However, effective in-well and reservoir surveillance is needed to understand steam conformance. Uniform steam chest development improves steam-oil-ratio (SOR) in continuous steam injection and accelerates recovery in cyclic steam injection. Conformance of the injected steam can be achieved by flow control devices (FCD) deployed on either tubing or liner. A new liner-deployed FCD was used in a horizontal steam injector in the Kern River field. The liner-deployed FCD is intended to replace the tubing-deployed FCDs while reducing capital costs, surveillance costs, and well intervention costs for conformance control. Fiber optics was used for surveillance, which is the most promising method in horizontal steam injectors considering reliability, accuracy, and cost. Fiber optic data enables monitoring the performance of liner-deployed FCDs as well as estimating the flow profile along the lateral length. Multi-mode Distributed Temperature Sensing (DTS) optical fibers and single-mode Distributed Acoustic Sensing (DAS) optical fibers were installed in the well for these objectives. Algorithms for interpreting DTS were improved to include a new technique, Shape Language Modeling (SLM), and a probabilistic approach. The configuration of the FCDs was changed during a well intervention, and it was monitored by DTS and DAS. Data from both DTS and DAS confirms the open/closed position of the sliding sleeve of FCDs initially and after the intervention. The probabilistic estimates of steam outflow in several FCD configurations match well with the theoretical outflow that is expected from the critical flow of steam through chokes installed in the FCDs.
Abstract Castillo1 suggested the use of the G-Function plot based on the work of Nolte2. It has been a standard practice in the fracturing community to estimate the fracture closing pressure from a tangent to the G*dp/dg plot. In this analysis technique, the assumption is that a fracture has already developed under the high-pressure fracturing fluid. Then when the pumping is relaxed, one can estimate the fracture closing pressure. In many California waterfloods, the issue of maximum allowable injection gradient has been debated. Various solutions have been proposed to calculate a safe injection gradient. One method that has been promoted is the application of the G-function plot. In this paper, we maintain that this application can be misleading using the prescribed cartesian G function plots. We present the results of an extensive research study for analyzing pressure fall-off data using the G-Plot function. We studied a reappraisal of the G function plot using waterflood conditions where no prior fractures had formed, and no fracture closing pressure was meaningful or applicable. We show from analysis of generated data, using both numerical reservoir modeling and analytical derivations for a radial flow system, that fall-off tests analyzed using the cartesian G function can generate false indications of fracture closing where in fact, the entire injection has been based on radial flow homogeneous injection systems. We also studied systems with a pre-existing fracture before injection. We show that if such a reservoir system is subjected to injection and fall-off tests, again, one may compute a false indication of the irrelevant fracture closure pressure. We discuss how the cartesian scale used for the G function plot can be misleading for the analysis of fall-off test data.
Abstract This paper is a contribution to failure prediction of unconsolidated intervals that could have a negative impact on injection efficiency because of susceptibility to structural changes under fluid injection processes. In unconsolidated formations, formation fines may be subjected to drag forces by injected water because of poor cementation. This results in small grain moments, and continuation can result in a gradual increase in permeability and eventual development of washed-out or thief zones. This paper presents a new modeling approach using information from profile surveys and grain and pore size distribution to model the process of injection and the induced particle movement. The motivation came from field observations and realization of permeability increase from profile surveys and substantial fines movement, leading to an increase in rock permeability. A series of case studies based on realistic published data on pore and grain size distribution are included to demonstrate the estimated increases in formation permeability. In our modeling approach, once we establish the range of grain sizes that fits the criterion for particle movement, a probabilistic algorithm, developed for the study, is applied to track changes in porosity and associated variations in permeability. This algorithm, presented for the first time, considers a stochastic approach to monitor the reservoir particle movements, pore size exclusion by particle accumulation and their resultant changes in rock properties. For this methodology, we ignored potential effects of wettability and clay swelling, and considered perfect spheres to represent the various grain sizes. Predictions made using various realizations of channel formation and petrophysical alterations show the significance of having access to three sources of information; pore size distribution, grain size distribution, and profile surveys. Through inverse modeling using these pieces of information for a particular formation, we demonstrate how we can predict realistic changes and map rock transport properties.
Abstract Implementing the IIoT paradigm into the classical oil & gas field OT systems is one of the essential concepts for Digital Oilfield 2.0. The transition in architecture and the corresponding technology changes can create a new cyber-physical security risk profile through alterations in the digital information structure of the oilfield OT system. With the onset of IIoT implementations in the industry, it is an opportune time to review and assess the emerging cyber-physical risk landscape. In the paper, we identified and compared the current oilfield OT logical structures with the designs emerging through the IIoT implementations. The analysis includes extensive reviews of developing standards, such as those proposed by Industrial Internet Consortium, and ongoing published experiences to find the primary points of transition. The security risks stemming from the IIoT implementation appear to raise significant concerns with regard to potentially severe cybersecurity outcomes, which could materially impact the integrity and safety of oilfieldoperations. The study concentrated on the cybersecurity threats that could pose negative physical and operational conditions resulting from loss of visibility and / or loss of control of the operational processes in field facilities. Extensive literature reviews were the basis for identifying the implications of cybersecurity risks in the ongoing stages of integrating the IIoT into the field. The reviews identified the modified strategies for cyber-physical systems, including potential threats and counter measurements for the field IIoT model. However, these proposed strategies still miss a fundamental denominator - the assessments generally ignore that it is the fundamental nature of IIoT structure itself that creates cyber-security vulnerabilities. To investigate further, we performed a contrasting analysis based on specific case studies of field IIoT devices such as the pump-off controller and OT architectures. Three foundational threat implications emerged on the transformation of IIoT architecture into the oilfield: 1)The exponential growth of connected distributed artificial intelligence (DAI) devices enormously increases the complexity of designing the software of each facility and system. 2)The cutting-edge Machine to Machine (M2M) characteristic in the IIoT model pushes the human out of the traditional control and monitor loop. 3)The widespread scale of DAI devices with the unique IP address in the network shifts cybersecurity risks to each connected endpoint. The cornerstone of the distinctive IIoT attributes illustrated in the paper contributes to the potential loss of control, leading to potential for serious damaging operational outcomes in the field. The goal of this paper is to aid oilfield security planning and design processes through animproved recognition of the cyber-physical security impacts emerging from the implementation of IIoT architectures and technologies integration into field OT domains.
Civan, Faruk (University of Southern California)
Summary This paper presents a theoretically rigorous correlation of the performance of capillary pressure and relative permeability of naturally fractured sandstone and carbonate reservoirs involving saturation shocks and loading/unloading hysteresis under various stress and thermal conditions. The proposed modeling approach accounts for the combined effects of the porous‐rock alteration by various processes, including deformation, transformation, deterioration, and collapse of pore structure, under prevailing temperature and stress conditions during loading and unloading processes, and their effect on the capillary pressure and relative permeability of naturally fractured reservoirs. A saturation shock causing a slope discontinuity in the capillary pressure and relative permeability is shown to occur during saturation change in some sandstone‐ and carbonate‐reservoir formations at a critical saturation condition. This phenomenon can be triggered by alteration of fluid‐percolation pathways as a result of the transition from open to closed natural or induced fractures and the deformation of pore structure. The effect of the saturation shock and loading/unloading hysteresis on the capillary pressure and relative permeability of reservoir‐rock formations is formulated by means of a phenomenological kinetics model and its applicability is demonstrated by analyzing and correlating the available experimental data. In this paper, the proven comprehensive model developed from a kinetics equation is shown to lead to a theoretically meaningful, universal, and practical constitutive equation in the form of a modified power law. This kinetics equation expresses the probability of dependence of a petrophysical property of porous rocks on a variable, such as saturation for capillary pressure and relative permeability, based on the value of the property relative to its low‐ and high‐end limit values. The applicability of the modified power‐law equation is validated by means of the experimental data of the capillary pressure and relative permeability gathered by testing of representative samples from various sandstone and carbonate reservoirs. The phenomenological parameters of the core samples obtained from sandstone and carbonate reservoirs are determined for best match of the experimental data with the modified power‐law equation. The value of the critical fluid saturation is determined by the observance of a slope discontinuity occurring in the measured experimental data of the variation of the capillary pressure and relative permeability with saturation. The scenarios presented in this study indicate that loading/unloading hysteresis and saturation shock have significant effects on the stress‐ and temperature‐dependent capillary pressure and relative permeability of the porous reservoir‐rock formations. The data‐inferred physics‐based model presented in this paper is proved to describe the stress‐ and temperature‐dependent capillary pressure and relative permeability of sandstone and carbonate rocks with high accuracy while meeting the endpoint‐limit conditions satisfactorily.
Javaheri, Mohammad (Chevron) | Tran, Minh (University of Southern California) | Buell, Richard Scot (Chevron) | Gorham, Timothy (Chevron) | Munoz, Juan David (Chevron) | Sims, Jack (Chevron) | Rivas, Stephen (Chevron)
Horizontal steam injectors can improve the efficiency of thermal operations relative to vertical injectors. However, effective in-well and reservoir surveillance are needed to understand steam conformance. Uniform steam-chest development improves the steam/oil ratio in continuous steam injection and accelerates recovery in cyclic steam injection. The conformance of the injected steam can be achieved by flow control devices (FCDs) deployed on either tubing or liner. A new liner-deployed FCD was used in a horizontal steam injector in the Kern River field. The liner-deployed FCD is intended to replace the tubing-deployed FCDs while reducing capital costs, surveillance costs, and well intervention costs for conformance control.
Fiber optics was used for surveillance, which is the most promising method in horizontal steam injectors considering reliability, accuracy, and cost. Fiber optic data enables monitoring the performance of liner-deployed FCDs as well as estimating the flow profile along the lateral length. Multimode distributed temperature sensing (DTS) optical fibers and single-mode distributed acoustic sensing (DAS) optical fibers were installed in the well for these objectives. Algorithms for interpreting DTS were improved to include a new technique, shape language modeling (SLM), and a probabilistic approach. The configuration of the FCDs was changed during the first well intervention, and it was monitored by DTS and DAS. Data from both DTS and DAS confirms the open/closed position of the sliding sleeve of FCDs initially and after the intervention. The probabilistic estimates of steam outflow in several FCD configurations match well with the theoretical outflow that is expected from the critical flow of steam through chokes installed in the FCDs.
Abstract Petroleum Engineers and Geoscientists are trained to offer substantive expertise in engineering the development of subsurface natural resources and the management of their production for commercial use. These professionals, by their educational training and experience, have specialized knowledge of subsurface geology, drilling, well completion, subsurface reservoir characterization, reservoir management, and production operations. They are the most qualified to take on the tasks of locating, mapping, selecting, monitoring, testing, and managing such operations. These professionals have experienced the pains and rewards of past several price cycles of oil and gas. The dependence of their employment opportunity on the inherent volatility of oil and gas prices has created extended periods of employment and career uncertainty, Adams-Heard, Rachel and Saraiva, Catarina: (2020). However, as we look to the future, new opportunities may be evolving for these professionals. In this paper, we will frame our discussion of the evolving nature of the career opportunities for petroleum engineers and geoscientists in the context of three key dimensions: –The Digital Transformation of the industry. –Changing educational requirements for petroleum engineering and geoscience. –Expanding career opportunities for petroleum engineers and geoscientists. The transformation taking place in oil and gas operations by digital technologies is perhaps the clearest example of both new opportunities and new challenges being presented to petroleum engineers and geoscientists. The content knowledge, specific expertise, and experience are essential for the successful application of rapidly advancing digital technologies, while at the same time displacing many traditional technical functions. The ongoing energy transition will alter the mix of future energy sources, and changes in supply and demand will like to continue the era of price volatility; however, hydrocarbons will continue to be a primary source of supply for the world's fuel and power needs. Critical domain expertise will continue to be needed for developing, operating, and abandoning oil and gas resources for many decades to come. The transformation of the energy supply chain will also create new opportunities, such as the re-purposing of subsurface structures to make them suitable for the storage of energy products or for the safe disposal of waste. The expertise need will heavily rely on this brand of graduates. This includes issues related to subsurface storage of natural gas, oil, and compressed air, hydrogen, and disposal of carbon dioxide and further focuses on the recovery of geothermal fluids as a non- hydrocarbon source of energy. Additionally, these subsurface specialists can help with managing the recovery of fresh subsurface waters for many communities. The future is also like to see the use of hydrocarbons as feedstocks for advanced industrial materials. In this study, we also discuss the role that the companies and government organizations can play to ensure attracting talent and maintaining the educational institutions essential for the professional development of subsurface experts who can address these important and evolving areas.