Progressive cavity pumps (PCP) have been used as artificial lift system for heavy oil lifting, low productivity wells and other challenging conditions which are common characteristics of brownfields. In addition to those conditions, there is the current complicated economic environment in which operating companies seek to reduce investments while enhancing field production operations with low-cost solutions aiming to increase the overall's field recovery factor. The initial step when trying to enhance field production operations in wells operating with PCPs as artificial lift system is performing a well-level analysis. During this analysis, the existing operational conditions and its corresponding production are evaluated. The continuity and accuracy of this analysis is highly dependent on the data input for analysis purposes. For instance, the rate of production is required as input and due to the nature of operation in brownfields, this value is not measured with the required frequency needed for performing a proper production enhancement analysis. This paper aims to provide a simple, automated, and accurate way to perform a calculated rate of production that is cost effective and easy to maintain, capable of being used during field production operations enhancement analysis, and applicable to wells operating with PCPs as artificial lift in heavy oil conditions, using regression and analytical methods. Both methods are being used part of a digital oilfield solution implemented in a heavy oil brownfield with telemetry-instrumented PCP wells. This solution is working inside a production operations platform that validates input data, manages different frequencies and types of data, and automatically calculates a production rate, which is then pushed to a visualization dashboard. Results provide an accurate production rate estimate suitable for reservoir engineering analyses while providing insight for the production operations enhancement.
The rich oil accumulations in the southern Tamaulipas area in Mexico have been discussed in the literature for over 100 years. The first productive well in this field located in north-east Mexico was drilled in 1910, and the field has been producing commercially since then. More than a 100 years later, in 2013, the field started a new chapter under a different operating company, which began a push for the implementation of an operations excellence initiative among the stakeholders for which the first goal is production maintenance through increased uptime of the wells. A key to success in this new chapter for the exploitation of the field is the implementation of a digital oilfield focused in linking operational philosophy with available technologies and telemetry systems to integrate the operations excellence initiative with the field's operational requirements. Five workflows are implemented and working for the field. Each workflow complies with a target: Well monitoring for progressive cavity pumps (PCPs): This workflow tackles the early detection of anomalies in operational variables for well performance. Well rate estimation for PCPs: This workflow calculates production rate estimates for PCP wells. Well status: This workflow provides the live determination of the well operational status. Production losses: This workflow provides the daily tracking of production performance. Integrated reservoir and production tracking: This workflow enables field-level integrated analysis for reservoir and production data. Incorporation of this solution generates a collaborative working environment between field operators, engineering departments and asset management, promoting synergy to strive for operation excellence in a challenging operating and economic environment. The implementation of this digital solution enables a new era for the operations of a 100-year-old brownfield in Mexico. Changing operational conditions and low-productivity wells producing with artificial lift systems are the key challenges to maintaining production in the field. The system allows for timely acknowledgement of the field operating conditions to take proactive actions thus strengthening the operations and supporting to meet the steadily growing production targets. The components of the system can be replicated and tailored to the challenges faced in different operating conditions. Field instrumentation, available technology, and engineering processes are combined to work toward the goal of excellence in operations and returns.
Integrated asset modeling has been used for the last decade with a wide technical application covering different challenges from field development to production optimization. Besides supporting the FEEDS and FEL studies for different purposes. Moreover, the technology has evolved in terms of integration and dynamic or transient simulation has been added as an extra element expanding the possibility to cover different challenges and workflows. The objective of this paper is to show how this dynamic integration (Dynamic integrated asset modeling) was applied to a common problem of several reservoirs that produce water and gas under different dynamic mechanisms (injection, aquifer and gas cap) to understand, from the reservoir perspective, the effects of gas and water conning over the entire production system. The methodology applied was using a refined sector model solved with numerical simulation and coupled with a transient multiphase flow simulator to see how pressure drop affect the contacts level and shape based on the petrophysical properties and under different production scenarios and generate different graphics to see how this phenomenon behaves. Besides a comparison with all the most analytical correlations used in the literature to identify gas and water conning was performed to see the differences among them and with this dynamic integrated approach. On the other hand, for the production side this coupled model was applied to an offshore facility to see these reservoir effects in the transport system and how they impact in the pipeline and riser due to this abrupt entrance of gas and water changing the flow conditions, flow patterns, pressure drop and creating some instabilities in the separators caused by severe slugging. The results of this analysis were very useful to understand the total production systems (reservoir-surface) behavior, predict the gas and water breakthrough, establish the critical rates to avoid these problems and see how the results differ in some cases with the common analytical correlations. Specific conditions in the pipeline and riser were established to quantify the slugging problems and evaluate different alternatives to eliminate the instabilities through proposing different scenarios such as gas injection in the riser, top side choking, etc. Application of this integrated approach has been very beneficial in recognizing the source of the problem, offer proper and feasible solutions in development and operational phases. In addition, validating and reducing uncertainty of related literature correlations and give to the production and reservoir engineers a quick and reliable way to know the critical rates that can support the decision-making process.
Increase recovery from mature oil reservoirs requires the definition of enhanced reservoir management strategies, involving the implementation of advanced methodologies and technologies in the field's operation. This paper presents a digital workflow enabling the integration of commonly isolated elements such as: gauges, flowmeters, inflow control devices; analysis methods and data, used to improve scientific understanding of subsurface flow dynamics and determine improved operational decisions that support field's reservoir management strategy. It also supports evaluation of reservoir extent, hydraulic communication, artificial lift impact in the near-wellbore zone and reservoir response to injected fluids and coning phenomenon. This latest is used as an example to demonstrate the applicability of this workflow to improve and support operational decisions, minimizing water and gas production due to coning, that usually results in increasing production operation costs and it has a direct impact decreasing reservoir energy in mature saturated oil reservoirs. This innovative workflow consists on the continuous interpretation of data from downhole gauges, referred in this paper as data-driven; as well as analytical and numerical simulation methodologies using real-time raw data as an input, referred in this paper as model-driven, not commonly used to analyze near wellbore subsurface phenomena like coning and its impact in surface operation. The resulting analyses are displayed through an extensive visualization tool that provides instant insight to reservoir characterization and productivity groups, improving well and reservoir performance prediction capabilities for complex reservoirs such as mature saturated reservoirs with an associated aquifer, where undesired water and gas production is a continuous challenge that incorporates unexpected operational expenses.
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