A Decade of Experience with MPFM in Northern Fields of Saudi Aramco
Abstract: Multiphase flow metering is considered one of the most essential technologies in well testing. Since the mid 1990's, Multiphase Flow Meters (MPFM) have evolved from a revolutionary new technology into a consolidated solution widely adopted by the major operators worldwide. This evolution has taken place thanks to the high quality of measurements, low operational cost and the capability of enabling remote monitoring of wells' performance and testing with ease. The installed MPFMs in Northern fiel… Show more
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 3 publications
References 4 publications
In order to find out the opportunities for cost saving, the focus must be directed to the main contributors in the overall cost. In Oil and Gas gathering facilities, one of the main contributors to the overall cost is how the gathering pipeline network is set up. Many field development options are available that depend on the nature of the development i.e. Pad design, Remote Manifolds Stations, and other designs that aim for cost saving. Pad design might be one of the best available options; however, it can be applied in the development of a green field gathering network, where a group of the wells are drilled in specific patterns. For the field where the wells are scattered, Pad design might not be the most cost-effective solution. The sharing of the flow lines is another practical approach that can be applied in, no matter, green or brown field gathering network development. However, one of the main challenges is the loss of production during well testing. This loss is mainly due to shutting down of one well while testing the other. Several options have been studied to compare the current practice of well's tie-in and testing verses the optimized and innovative idea of the flow lines sharing with the consideration of "All-in-One" Multi-phase Flow Meter (MPFM) at the Well head for well testing. Option-1 in brief is to construct a number of new gathering stations and tie-in the wells via individual single flow lines to these stations, while the concept of Option-2 is to use the spare capacities in the existing flow lines and transfer lines to tie-in the new wells to the nearest and close by existing wells. The local MPFM's will be deployed on both new and existing wellheads. If NO spare capacities are available in the existing transfer lines between the gathering stations and central gathering station, then Option-3 is the best fit which is the construction of less number of gathering stations than Option-1 while adopting the concept of flow line sharing and having local MPFM's at the each of the well heads. These options have been evaluated according to ADNOC four pillars comprising of people, performance, profitability and efficiency emphasizing on and without compromising the HSE and asset integrity. The importance of adequacy checks and maximizing the utilization of existing facilities is a "must do" in the current market condition in order to get the maximum return from what has been spent earlier. The results showed that, sharing of the flow lines by combining the flow of two wells has a very high cost benefit verses having individual flow lines per well. The drawback of production losses will be recovered by the deployment of MPFM's at each individual wellhead that provides the well production test data all the time. Therefore, the optimized approach of Oil gathering network will enable the forthcoming projects to move forward with development and get more production with less investment. Though sharing of flowlines with MPFM's at wellheads seems to be the best approach, its direct implementation poses certain challenges because of the current design of MPFM's that require infrastructure (such as power availability) constraints at remote wellhead locations. This paer highlights the need of industry to work and develop a design of MPFM's that minimizes or eliminates such constraints to make this technology widely acceptable in such applications.
In order to find out the opportunities for cost saving, the focus must be directed to the main contributors in the overall cost. In Oil and Gas gathering facilities, one of the main contributors to the overall cost is how the gathering pipeline network is set up. Many field development options are available that depend on the nature of the development i.e. Pad design, Remote Manifolds Stations, and other designs that aim for cost saving. Pad design might be one of the best available options; however, it can be applied in the development of a green field gathering network, where a group of the wells are drilled in specific patterns. For the field where the wells are scattered, Pad design might not be the most cost-effective solution. The sharing of the flow lines is another practical approach that can be applied in, no matter, green or brown field gathering network development. However, one of the main challenges is the loss of production during well testing. This loss is mainly due to shutting down of one well while testing the other. Several options have been studied to compare the current practice of well's tie-in and testing verses the optimized and innovative idea of the flow lines sharing with the consideration of "All-in-One" Multi-phase Flow Meter (MPFM) at the Well head for well testing. Option-1 in brief is to construct a number of new gathering stations and tie-in the wells via individual single flow lines to these stations, while the concept of Option-2 is to use the spare capacities in the existing flow lines and transfer lines to tie-in the new wells to the nearest and close by existing wells. The local MPFM's will be deployed on both new and existing wellheads. If NO spare capacities are available in the existing transfer lines between the gathering stations and central gathering station, then Option-3 is the best fit which is the construction of less number of gathering stations than Option-1 while adopting the concept of flow line sharing and having local MPFM's at the each of the well heads. These options have been evaluated according to ADNOC four pillars comprising of people, performance, profitability and efficiency emphasizing on and without compromising the HSE and asset integrity. The importance of adequacy checks and maximizing the utilization of existing facilities is a "must do" in the current market condition in order to get the maximum return from what has been spent earlier. The results showed that, sharing of the flow lines by combining the flow of two wells has a very high cost benefit verses having individual flow lines per well. The drawback of production losses will be recovered by the deployment of MPFM's at each individual wellhead that provides the well production test data all the time. Therefore, the optimized approach of Oil gathering network will enable the forthcoming projects to move forward with development and get more production with less investment. Though sharing of flowlines with MPFM's at wellheads seems to be the best approach, its direct implementation poses certain challenges because of the current design of MPFM's that require infrastructure (such as power availability) constraints at remote wellhead locations. This paer highlights the need of industry to work and develop a design of MPFM's that minimizes or eliminates such constraints to make this technology widely acceptable in such applications.
In this study, we aim to demonstrate how machine learning can empower computational models that can predict the flow rate of a given well. Given current real-time data and periodic well tests, this new method computes flow rates using data-driven model. The computational model is based on analyzing the relations and trends in historical data. Relational databases include huge amounts of data that have been accumulated throughout decades. In addition, there is a large number of incoming operational data points every second that gives a lot of insight about the current status, performance, and health of many wells. The project aims to utilize this data to predict the flow rate of a given well. A variety of well attributes serve as inputs to the computational models that find the current flow rate. Artificial Neural Networks (ANN) were used in order to build these computational models. In addition, a grid search algorithm was used to fine-tune the parameters for the ANN for every single well. Building a single unique model for every well yielded the most accurate results. Wells that are data-rich performed better than wells with insufficient data. To further enhance the accuracy of the models, models are retrained after every incoming patch of real-time data. This retraining calibrates the models to constantly represent the true well performance and predict better. In practice, Flow rate prediction is used by production engineers to analyze the performance of a given well and to accelerate the process of well test verification. One of the main challenges in building unique models for every well is fine-tuning the parameters for the artificial neural networks, which can be a computationally intensive task. Parameter fine-tuning hasn't been discussed in previous literature regarding flow rate prediction. Therefore, our unique approach addresses the individuality of every well and builds models accordingly. This high-level of customization addresses the problem of under-fitting in ANN well models.
Overcoming Challenges of Testing Gas Lifted Wells Via Multiphase Flowmeters with a Novel Work-Process Approach Embedded in a Digital Outlook to Enhance Well Test Data Quality. Lesson Learned from a Smart Field in Abu Dhabi
Multiphase flow meter's (MPFM) reliability is a challenge that several oil operators face continuously. Many companies adopt this option attracted by its operational flexibility and cost saving proposition, when testing facilities must have minimum footprint or/and remote operational cases, demanding continued monitoring. However, to succeed, they will require dedicated personnel to monitor their performance, significant investment in instrumentation to allow remote operations, additional surveillance activities and quality-checks routines to maintain 2-10% accuracy. Moreover, subsurface complexity led to larger uncertainty and deviations in production reconciliation. This case study is presented in one smart field located in Abu Dhabi, composed by tight reservoirs with strong compositional gradient, with saturation pressure ranging from 1000 to 3600 psi along with a large areal and vertical solution gas variation. On the other hand, the EOR program has been in place for the last 40 years, injecting WAG and CO2 in inverted patterns with potential breakthrough in producers. The majority of the wells were commissioned with gas lift, as they were not able to flow naturally; therefore, produced gas will be indirectly estimated from total produced gas. Limited PVT reports are used as reference across field while common PVT data is used in neighbor wells located few Kms away. Furthermore, surface facilities were newly commissioned, adding additional uncertainties anticipated from new projects, which reliability is represented as a "bath-type curve" with expected high-failure rate at the beginning, followed by a failure reduction after some maturity and understanding is achieved; and finally, it will escalate due to equipment wear out. Therefore, early systematic errors with regard to meters configuration, design, data-streaming and data-inputs were found and corrected. Wells are controlled remotely and are equipped with surface pressure and temperature transmitters that can be monitored from the office for production optimization efficiency. The asset deals with different MPFM providers and technology principles such as: dual-gamma source, single-gamma source and non-radioactive sources to be learned in a very short time. 70% of the flow-tests performed via MPFM were rejected due to anomalies in GOR or rates over-prediction, identified by a 20% additional oil production compared with export fiscal meters. It can be seen that GOR anomalies correction was not obvious, as it represents a multidimensional problem with several sources of errors to investigate. This paper presents the lesson learned from the implementation of real-time monitoring techniques on MPFM to evaluate its performance and troubleshooting, focusing on a novel and simple methodology of root cause analysis with smart analytics, including comparison with continues physics and AI based Virtual Meters, integrated with auto-diagnostic system, allowing optimum allocation of field resources while minimizing vendor intervention, with implicit cost saving. This novel approach provided a quick problem detection enabling the asset to improve its well test acceptance from 50 to 92% due to MPFM reliability improvement. The presented methodology also opened the door to introduce real time gas lift and production optimization exploiting direct measurements of MPFM parameters such as GVF, permittivity and mix-densities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
Contact Info
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.
