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Nicholson, A. Kirby (Pressure Diagnostics Ltd.) | Bachman, Robert C. (Pressure Diagnostics Ltd.) | Scherz, R. Yvonne (Endeavor Energy Resources) | Hawkes, Robert V. (Cordax Evaluation Technologies Inc.)
Abstract Pressure and stage volume are the least expensive and most readily available data for diagnostic analysis of hydraulic fracturing operations. Case history data from the Midland Basin is used to demonstrate how high-quality, time-synchronized pressure measurements at a treatment and an offsetting shut-in producing well can provide the necessary input to calculate fracture geometries at both wells and estimate perforation cluster efficiency at the treatment well. No special wellbore monitoring equipment is required. In summary, the methods outlined in this paper quantifies fracture geometries as compared to the more general observations of Daneshy (2020) and Haustveit et al. (2020). Pressures collected in Diagnostic Fracture Injection Tests (DFITs), select toe-stage full-scale fracture treatments, and offset observation wells are used to demonstrate a simple workflow. The pressure data combined with Volume to First Response (Vfr) at the observation well is used to create a geometry model of fracture length, width, and height estimates at the treatment well as illustrated in Figure 1. The producing fracture length of the observation well is also determined. Pressure Transient Analysis (PTA) techniques, a Perkins-Kern-Nordgren (PKN) fracture propagation model and offset well Fracture Driven Interaction (FDI) pressures are used to quantify hydraulic fracture dimensions. The PTA-derived Farfield Fracture Extension Pressure, FFEP, concept was introduced in Nicholson et al. (2019) and is summarized in Appendix B of this paper. FFEP replaces Instantaneous Shut-In Pressure, ISIP, for use in net pressure calculations. FFEP is determined and utilized in both DFITs and full-scale fracture inter-stage fall-off data. The use of the Primary Pressure Derivative (PPD) to accurately identify FFEP simplifies and speeds up the analysis, allowing for real time treatment decisions. This new technique is called Rapid-PTA. Additionally, the plotted shape and gradient of the observation-well pressure response can identify whether FDI's are hydraulic or poroelastic before a fracture stage is completed and may be used to change stage volume on the fly. Figure 1: Fracture Geometry Model with FDI Pressure Matching Case studies are presented showing the full workflow required to generate the fracture geometry model. The component inputs for the model are presented including a toe-stage DFIT, inter-stage pressure fall-off, and the FDI pressure build-up. We discuss how to optimize these hydraulic fractures in hindsight (look-back) and what might have been done in real time during the completion operations given this workflow and field-ready advanced data-handling capability. Hydraulic fracturing operations can be optimized in real time using new Rapid-PTA techniques for high quality pressure data collected on treating and observation wells. This process opens the door for more advanced geometry modeling and for rapid design changes to save costs and improve well productivity and ultimate recovery.
The purpose of the digital oilfield is to maximize oilfield recovery, eliminate non-productive time, and increase profitability through the design and deployment of integrated workflows. Digital oilfield workflows combine business process management with advanced information technology and engineering expertise to streamline and, in many cases, automate the execution of tasks performed by cross-functional teams. The term "digital oilfield" has been used to describe a wide variety of activities, and its definitions have encompassed an equally wide variety of tools, tasks, and disciplines. All of them attempt to describe various uses of advanced software and data analysis techniques to improve the profitability of oil & gas production operations. If one maps the challenges onto the themes, it becomes clear that digital oilfields are attempting to compensate for a higher complexity and cost of operations which must be performed by fewer, less experienced employees.
Exhaust plumes from generators, pumps, and compressors aboard offshore platforms pose a hazard to crew and equipment. Mitigation for exhaust-plume impingement has traditionally been achieved by locating the exhaust uptake away from sensitive areas of the platform by use of long horizontal duct runs, by use of a very tall exhaust stack ( 20 m), or by some combination of the two. These solutions result in an exhaust system that is complicated to design and that adds significant weight to the platform. A more practical and weight-efficient alternative exists in the form of plume cooling. Plume-cooling technology has been in use for more than 40 years on military ships for the purpose of infrared-signature suppression and for the protection of sensitive weapons and communications systems that would otherwise be damaged by hot impinging exhaust gases.
The Internet of Things (IoT) has become a popular phrase as companies in various industries look to consolidate and streamline their operations. For upstream oil and gas operators, an IoT infrastructure may present an opportunity improve quality control on their projects, potentially reducing costs and increasing production, an expert said. At a presentation held by the SPE Gulf Coast Section's Research and Development Study Group, Setrag Khoshafian discussed emerging trends with IoT-based systems, as well as the challenges operators may face in implementing them. Khoshafian is the vice president of business process management technology at Pegasystems. The IoT is the connection of physical devices to a network so that each device can collect and exchange data.
As new technologies, environmental concerns, and consumer priorities disrupt the status quo of energy operations, industry has begun to rethink how it must proceed in order to remain as vital to global development in the future as it is today. But what does rethinking entail? Does the industry need to transition much to adapt to a new reality, or will success in the future be a simple matter of changing perceptions? How much will industry need to continue leveraging innovative technologies to survive in the future? Those questions have been at the forefront of several discussions held in recent months.
Abstract Underperforming fractured wells are often represented by fracture face damage or choked fracture models. This study shows a different pressure behavior identified from various historical cases in which mixed low- and high-mobility regions are present after hydraulic fracturing. Using available technology and processes to optimize the hydrocarbon production from wells in mature fields, this paper presents the data analyses and methodology used to analyze and discretize the induced damage after the stimulation process. Production performance and pressure buildup data showed anomalous behavior in hydraulically fractured wells. To define this problem, an additional detailed reservoir simulation was performed to reproduce the damage mechanism that was not initially well identified by the pressure/derivative analysis. Various cases were examined to define the damage type, extent, and mobility changes present around the fractured area. Results from these simulations were used in pressure transient analysis software to generate analytical models that mimic the pressure behavior. The analytical models were compared with downhole data registered during well evaluation for validation. Numerical models demonstrated that a low-mobility region was present around the fracture face and more consistent productivity results can be achieved by avoiding the creation of this region during fracture jobs by combining different breakers (delayed, temperature-activated, and fast reaction). Pressure buildup data registered from different wells confirmed that the low-mobility region was not present.
Abstract This paper will describe the success of Chevron Pacific Indonesia's (PT. CPI) Sumatera Operation (SMO) to deliver improved business results through the implementation of an Integrated Optimization Decision Support Center (IODSC). The SMO IODSC is focused on value optimization across the Rokan Production Sharing Contract (PSC) by developing and implementing digital solutions ranging from the simple, such as Short Message Service (SMS) gateway to monitor rig status, through to the more advanced, such as Artificial Intelligence to identify failing equipment. Value creation was achieved by the systematic adoption of digital solutions to reduce lost production opportunity (LPO), reduce expenses, improve energy efficiency and optimize hydrocarbon production. Key to this systematic adoption is IODSC's Integrated Exception Management (IEM) system. IEM supports CPI employees in their daily tasks by: Managing large amounts of data captured each day and using data science to change it to actionable information. Capturing exception criteria based on Subject Matter Experts (SME) knowledge that automatically identifies and prioritizes wells and equipment operating outside the desired condition (exception signals). Housing workflows to enable review, action and close-out of the exception signals. IEM provides "one-stop exception review" and "start to finish workflow" capabilities that documents accountability for each step of the workflow and the time taken to complete. IEM allows for the exception criteria to be defined by physical principles, subject matter expert (SME) knowledge, or Artificial Intelligence (AI)-based techniques. As a result of this systematic implementation of improved workflows and digital solutions, within 2 years of commencement the IODSC exceeded it's 5 year value creation target.
Wibawa, Ramdhan (PT Chevron Pacific Indonesia) | Handjoyo, Teguh (PT Chevron Pacific Indonesia) | Prasetyo, Joko (PT Chevron Pacific Indonesia) | Purba, Monas (PT Chevron Pacific Indonesia) | Wilantara, Dedi (PT Chevron Pacific Indonesia) | Dongoran, Japet (PT Chevron Pacific Indonesia) | Gunawan, Gunawan (PT Chevron Pacific Indonesia) | Negara, Ari (PT Chevron Pacific Indonesia)
Abstract Sucker Rod Pumps (SRP) have been extensively utilized in the Duri field Heavy Oil Operations Unit (HOOU) for more than 6000 production wells. Approximately 2000 of these wells are equipped with dynamometer online that generates a daily dynamometer card (DC). Historically, the pump cards evaluation has led to the identification of several mechanical pump issues such as a traveling valve and standing valve leak that directly impact production. One step of the traditional process to identification of rod pump failure is based on a manual pump card shape analysis performed for individual wells by different engineers throughout production history. To improve efficiency and reliability of shape analysis, Artificial Intelligence-based data analysis has been recently integrated in the oil and gas industry. This article proposes an approach to pump card classification, developed by the Integrated Optimization Decision Support Center, using a modified Case-Based Reasoning or computer reasoning by analogy approach where new problems are solved by comparison to analogous problems solved in the past. The proposed methodology begins with definition of a reference DC for every known type of mechanical failure. The reference cards define the analogy set. Actual pump cards are then normalized and compared for similarity against each reference card or analogy using Euclidean distance measure between the actual and reference cards. For each actual pump card, the output of this approach is a set of similarity scores which indicate the pump failure type corresponding to references card shape, if any. The analysis is enhanced through the addition of rules based on pump operational parameters that result in specific pump failure signals. The methodology has been verified against DC evaluations from Subject Matter Experts (SME) and is demonstrated to provide robust pump failure signals more efficiently than by manual interpretation of DC for a series of individual wells.
Computer-controlled drilling is slowly changing how the oil and gas industry discovers natural resources. Automated drilling can reduce the number of injuries to zero and increase productivity and accuracy. Global oil prices and a surplus of gas have caused an improvement in the economics of automated projects. Meanwhile, in North America, human-operated drilling has greatly improved. According to a 2011 issue of Drilling Contractor, the first generation of Shell's automated control system already showed a 70% improvement in rate of penetration (ROP) in test areas.
The generic term "intelligent well" is used to signify that some degree of direct monitoring and/or remote control equipment is installed within the well completion. The first computer-assisted operations optimized gas lifted production by remote control near the tree and assisted with pumping well monitoring and control. Permanent downhole pressure and temperature gauges are commonly run as part of the completion system and combined with data transmission infrastructure. With the development, successful implementation, and improving reliability of a variety of permanently installed sensors, it was perceived that the potential to exercise direct control of inflow to the wellbore would provide significant and increased economic benefit.