The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
- Data Science & Engineering Analytics
The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
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Chen, Qiang (RIPED, PetroChina Co. Ltd, Beijing, China) | Hao, Zhongxian (RIPED, PetroChina Co. Ltd, Beijing, China) | Huang, Shouzhi (RIPED, PetroChina Co. Ltd, Beijing, China) | Gao, Yang (RIPED, PetroChina Co. Ltd, Beijing, China) | Wei, Songbo (RIPED, PetroChina Co. Ltd, Beijing, China)
Shale oil had attracted worldwide attention due to its vast volume, according to statistics, technical recovery of shale oil worldwide exceeded 250billion ton, mostly located in America, Africa and north Asia. However shale oil was characterized by its high viscosity, deep reservoir location, posing threats to the operator, traditional rod-pump artificial lift was not a good choice due to the friction issue, How to walk out of those challenges were worth thinking, while rod free artificial lift methods had been field proven in the oilfield, its progress would give us some inspirations. In this paper, rod free artificial lift methods including downhole motivated reciprocating pump, centrifugal pump and progressing cavity pump were discussed, some technological highlights such as pulling and running electric cables, host SCADA system and production control algorism had been introduced in detail. Finally the efficacy of rodless artificial lift was analyzed from the perspective of investment
Al-Ballam, S. (Kuwait Oil Company, Ahmadi, Kuwait) | Karami, H. (Mewbourne School of Petroleum & Geological Engineering, The University of Oklahoma, Norman, OK, USA) | Devegowda, D. (Mewbourne School of Petroleum & Geological Engineering, The University of Oklahoma, Norman, OK, USA)
Abstract Electrical submersible pumps (ESPs) are among the most common artificial lift techniques in highly productive oil wells. The ESP failures are extremely costly to the producers and must be minimized. This study proposes a hybrid approach utilizing multi-class classification machine learning (ML) models to identify various specific failure modes (SFMs) of an ESP. A comprehensive dataset and various ML algorithms are utilized, considering the physics of fluid flow through the ESP. The ML models are based on field data gathered from the surface and downhole ESP monitoring equipment over five years of production of 10 wells. The dataset includes the failure cause, duration of downtime, the corresponding high-frequency (per minute) pump data, and well-production data. The prediction periods of 3 hours to 7 days before the failure are evaluated to minimize false alarms and predict the true events. Four modeling designs are used to handle the data and predict ESP failure. These designs differ in the input parameters used for the model and signify the effect of including the physical parameters in failure prediction. Several ML models are tested and evaluated using precision, recall, and F1-score performance measures. The K-Nearest Neighbor (KNN) model outperforms the other algorithms in forecasting ESP failures. Some other tested models are Random Forest (RF), Decision Tree (DT), Multilayer Perceptron (MLP) Neural Network, etc. According to the data, most ESP operational failures are characterized as electrical failures. The ML models show similarly good performances with high true prediction rates in predicting ESP failures for all the tested designs. The design that integrates the effects of gas presence and pump efficiency while minimizing the number of input variables is suggested for general use. Increasing the prediction period up to 3 days results in a negligible drop in the model’s performance, showing that the model can predict ESP failures accurately three days before their occurrences. However, the forecasts show increases in missed failures and false alarms for prediction periods of more than three days, making three days the selected prediction period. These ML models will aid operators in avoiding undesirable events, reducing downtime, and extending the lifespan of ESPs. ESP failures are unanticipated but common occurrences in oil and gas wells. It is necessary to detect the onset of failures early and prevent excessive downtime. This study’s model allows engineers to detect failures early, diagnose potential causes, and propose preventive actions. It is crucial in transitioning from a reactive event-based to proactive and predictive maintenance of artificial lift operations.
Yushchenko, T. S. (Gazpromneft—Technological Partnerships (Corresponding author)) | Demin, E. V. (Gazpromneft—Science and Technology Center) | Khabibullin, R. A. (Gazpromneft—Science and Technology Center) | Sorokin, K. S. (Gazpromneft—Technological Partnerships) | Khachaturyan, M. V. (Gazpromneft—Palyan) | Baykov, I. V. (Gazpromneft—Technological Partnerships) | Gatin, R. I. (Gazpromneft—Technological Partnerships)
Summary In this study, unique field data analysis and modeling of operating wells with an extended horizontal wellbore (HW) and multistage hydraulic fracturing (MHF) in the Bazhenov formation were conducted. Moreover, a large amount of long horizontal well data obtained from the Bazhenov formation field was used. Wells with extended HW drilling and MHF are necessary for commercial oil production in the Bazhenov formation. Problems can occur in such wells when operating in the flowing mode and using an artificial lift at low flow rates. This study aimed to describe the field experiences of low-rate wells with extended HWs and MHF and the uniqueness of well operations and complexities. It was also focused on modeling various operation modes of such wells using specialized software and accordingly selecting the optimal downhole parameters and analyzing the sensitivity of fluid properties and well parameters to the well flow. The flow rates in wells with extended HW and MHF decrease in the first year by 70–80% when oil is produced from ultralow-permeability formations. Drainage occurs in a nonstationary mode in the entire life of a well, leading to complexities in operation. A comprehensive analysis of field data [downhole and wellhead pressure gauges, electric submersible pump (ESP) operation parameters, and phases’ flow rate measurements] and fluid sample laboratory studies was conducted to identify the difficulties in various operating modes. For an accurate description of the physical processes, various approaches were used for the numerical simulation of multiphase flows in a wellbore, considering the change in the inflow from the reservoir. The complexities that may arise during the operation of wells were demonstrated by analyzing the field data and the numerical simulation results. The formation of a slug flow in low flow rates in a wellbore was caused by a rapid decline in the production rate, a decrease in the water cut, and an increase in the gas/oil ratio (GOR) over time. Based on the results, proppant particles can be carried into the HW and thereby reduce the effective section of the well in case of high drawdowns in the initial period of well operation. Consequently, the pressure drops along the wellbore increased, and the drawdown on the formation decreased. Other difficulties were determined to be associated with the consequences and technologies of hydraulic fracturing (HF). These effects were shown based on the field data and the numerical simulation results of the flow processes in wells. In addition, corrective measures were established to address various complexities, and the applications of these recommendations in the field were conducted.
Yan, Lai Wai (Petronas Malaysia Petroleum Management) | Gupta, Mukesh (Petronas Malaysia Petroleum Management) | Tajuddin, Nazim Musani (Petronas Malaysia Petroleum Management) | M Diah, M Amri B (Petronas Malaysia Petroleum Management) | Shah, Jamari M (Petronas Malaysia Petroleum Management) | Masoudi, Rahim (Petronas Malaysia Petroleum Management) | Mokhtar, Syahrini Bt (Petronas Malaysia Petroleum Management)
Abstract This paper entails the profitable development of an offshore small oil reservoir. Offshore technologies are expensive and require higher capital expenditures (CAPEX) and operating expenses (OPEX) due to the need for advanced technologies for drilling, production, and environmental protection. Generally, reservoirs with large reserves are considered for large capital investments. However, this paper demonstrates how accurate reservoir description in conjunction with advanced offshore technologies can help to develop small offshore fields economically. These technologies are deployed in an integrated manner (surface and subsurface) to develop such fields. Offshore logistics for production facility maintenance increases the OPEX due to the transportation of personnel and equipment to and from the site. Offshore production systems have higher CAPEX due to specialised offshore equipment, including sub-sea equipment. Other than higher costs, the oil price volatility makes it difficult to plan for long-term production to recover the cost. Therefore, offshore fields have several challenges, e.g., logistical, technical, environmental, economic, and safety. However, collaborations and partnerships between industry and government help to share the project's economic risk. Cost can be further reduced through new development, production, and reservoir characterisation technologies to manage offshore development and operations costs. Production is enhanced through advancement in well construction and production systems to support high OPEX of floating production, storage, and offloading system.
Devshali, Sagun (Oil & Natural Gas Corporation Ltd.) | Nischal, Rajiv (Oil & Natural Gas Corporation Ltd.) | Prasad, BVRV (Oil & Natural Gas Corporation Ltd.) | Yadav, M (Oil & Natural Gas Corporation Ltd.) | Vamsi, Paipuri (Oil & Natural Gas Corporation Ltd.) | Uniyal, Rishabh (Oil & Natural Gas Corporation Ltd.) | Kumar, Manish (Oil & Natural Gas Corporation Ltd.)
Abstract Field Alpha is situated about 200 km West of Mumbai city in a Deep Continental Shelf at the water depth of 85 - 90 m. The existing facilities consists of 5 Well Head Platforms (WHP) connected to FPSO through a subsea PLEM and riser system. A total of 36 wells from 5 well head platforms in the field are producing 61348 blpd with an average water cut of 68%. All these 36 wells are producing through Electric Submersible Pump which is one of the most effective and economical means of lifting large volumes of liquid. The current paper is an attempt to address various issues pertaining to Electrical Submersible Pumps in the offshore field using well wise Nodal Analysis and Integrated Production Modelling. In the field under study, as the production volumes per well are high, failure of even one ESP leads to substantial production loss till the system is replaced by work over operation. Failure in the ESP system generally occurs due to one or a combination of issues related to reservoir inflow, fluid properties, design, completion, electrical components and experience of manpower. On the basis of system analysis, requisite optimization/ intervention measures proposed to improve performance of ESPs along with network debottlenecking results have been discussed in the paper. As per the analysis, scope exists in 7 wells for production enhancement. The envisaged incremental production from these wells has been found to be 1653 blpd considering current reservoir pressure and water cut. In 7 wells, ESPs have been found to be operating either in upthrust or are tending towards upthrust. These wells have potential to produce more but due to limitations of the existing pump capacities, the maximum drawdown is restricted. In 6 wells, ESPs have been found to be operating in downthrust. These wells have separately been assessed for wellbore performance. Additionally, Integrated Production Modelling indicated that the node pressure at each Well Head Platform are within the ESP design pressure limits. On the basis of the study, few of the recommended measures have already been implemented in the field and have resulted in a liquid gain of 335 blpd (139 bopd).
Abstract Deep-seabed mud containing a high concentration of rare-earth elements, including yttrium, has been discovered in the western North Pacific Ocean near Minami-Torishima Island, Japan. However, production of the rare-earth rich mud is challenging because of its location at water depths of over 6000 m. We propose a new subsea lifting system for deep-seabed rare-earth rich mud. The lifting system consists of a small diameter marine riser and an inner work string. At the lower end of the work string, a hydraulic jet pump is equipped so that rare-earth rich mud slurry can be easily sucked from a sea-bottom mud collecting device and lifted through the riser annulus. The jet pump is driven with power fluid pumped from a floating mining vessel. To evaluate the suction performance of the jet pump and the flow assurance in the annulus, numerical simulations were performed for various kinds of power fluid rates and jet pump configurations. The simulation results suggested that the proposed lifting system could, in principle, lift slurry containing rare-earth rich mud continuously to a surface floating vessel. Also, the hydraulic jet pump mechanism could be optimized to maximize the suction caused by the Venturi depressurization effect and to achieve a commercially feasible mud lifting rate of 3500 ton/day. For a pump configuration with three pairs of diffusers and suction lines, a drive fluid flow rate of 700 gal/min was found to be sufficient to meet the economic production criteria.
This course will help develop a solid foundation in all forms of lift and the concepts of the selection process to maximize production and return on investment. Half Day or 1 Day (The course length may be adjusted to meet the learning level of the target audience.) This class helps ensure a broad view of artificial lift, particularly when in-house expertise is limited to one-or two-lift systems. This course is for production and field operations engineers, junior and senior petroleum engineers and field technicians as well as geoscientists and reservoir engineers who wish to understand the implications of production systems on their field reservoirs. CEUs (Continuing Education Units) are awarded for this half-day or 1-day course.
In this hands-on course, the participants will learn some of the techniques and workflows applied to artificial lift and production while reviewing code and practicing. The focus will be on the development of data-driven models while reviewing the underlying artificial lift principles. After introducing data science and analytics techniques, the course will discuss some business use cases that are amenable to data-driven workflows. Two or three problems will be presented during the training. For each case there will be a demonstration of the solution of such a problem using a data analysis technique with Python code deployed in the Google-cloud.
Ali, Ahmed Maher (Gulf of Suez Petroleum Company) | Negm, Mohamed Nagy (SLB) | Darwish, Hatem Mohamed (SLB) | Mansour, Khaled Mohamed (SLB)
Abstract Offshore gas-lifted wells are challenging due to the numerous factors affecting performance, starting from the surface gas compression facility to reservoir performance. Mature oil fields add more challenges due to many flow assurance and mechanical problems. Real-time well monitoring is a must for early problem identification. Also, performance modeling is powerful and helpful for identifying and rectifying problems early. The work here emphasizes an optimization strategy for offshore gas-lifted wells. This paper introduces cases of offshore problematic gas-lifted wells and their full optimization and problems solving strategy to be utilized as an integrated approach for solving the problems of similar problematic gas-lifted wells in any field. The recommended strategy depends on studying problematic gas-lifting wells covering some commonly encountered problems. The recommended remedial actions for the selected problematic cases in this intensive study resulted in precious oil gains, cost savings, and gas lift usage optimization. The solution combines surveillance, multiphase simulation, data analytics, and operations. This paper discusses three major problems and the strategy to solve them: the first is wells with erroneous surface gas measurement and excessive gas injection; the second is unstable gas-lifted wells, and the third is optimizing low reservoir deliverability gas-lifted wells. In addition, other individual optimization cases, including integrated full-field cases, are introduced for the recommended strategy's completeness. This comprehensive study finds that the optimum approach for rectifying most gas-lifted wells problems must start with real-time monitoring, then modeling the case, and end by recommending possible solution scenarios and their impact on optimizing well performance. This study brings the significance of surveillance and dynamic simulations in the overall production cycle: planning to operations. Further, dynamic simulations also help arrive at operators’ guidelines on avoiding failed start-ups and ensuring stable operation. Finally, the power of integration between different disciplines is shown by incorporating several subsurface and surface information in the uncertainty study.
Abstract Gas Lift has been applied in the oil field for more than 70 years, despite the new technology and developments there is always more optimization that can be done. In this paper we are giving a leading example of one of the oldest gas lift projects in gulf of Suez that has been running for more than 50 years where 540 MMSCFD being pumped on daily basis to produce more than 200 wells as of today. the experience in this field is quite historical but the question is always persisting are we making best use of lift gas volumes and pressure, does every well have the optimum design and receives the optimum gas lift rate. One more important question will be how to prioritize interventions and optimization operations to target wells with highest value. In order to assess the overall gas lift performance of the field an innovative dashboard was created including Key performance indicators that reflect benchmarking of Lift Gas Consumption compared with historical Performance of the field. This should spot the light to the field with lowest efficiency and most probably it is expected higher return of production if we dedicate efforts to this field. Moreover creating wells dashboard has valued new Key Performance indicators with New Diagnostic Graphs that was not given attention by the industry before. Having these diagnostic Plots allowed benchmarking performance of wells for similar reservoir, completion type, gas lift design and sand face completion. Using this technique, it became easy to detect wells with higher potential of production with proper gas lift intervention. Although Analytics can give some guidance on the required actions to enhance production of wells knowing the basic design, having the analytics coupled with Integarated Network modelling and well models added more value to the project. Data Driven Gas Lift Optimization approach was applied since Oct. 2021 in an extensive approach over GOS, the approach succeeded to define more than 74 Optimization and Intervention Opportunities 45 of them were actually intervened in less than a year and added more than 4000 BOPD to production capacity. It was not a surprise that some of historically known underperforming wells were interpreted underperforming for other reasons than gas lift in-efficiency but using Gas lift Analytics re-analysis of the system showed huge value for gas lift intervention in these wells and succeeded to revive them. Data Analytics and Data driven gas lift optimization is proved a huge leap in managing gas lift fields and keeping the system running closer to optimum.