Online Asset Optimization Initiatives in Pemex Midstream

Villaseñor, Robles; Paz, Pedro; Trujillo, Emilio Sampayo; García, Lomgimar Lombardo; Franco, Francy; Useche, Marcos; Narváez, Shirley Estefanía Moreira; Karimi, Hossein; Rossi, David J.; Pitts, Kirk

doi:10.2118/173427-ms

Cited by 4 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dynamic (transient) modeling has been extensively used in industry for the past several decades to predict and analyze problems that involve multiphase fluid flow (Ostos Villasenor 2015). Dynamic multiphase flow simulators enable engineers to look at flow assurance and operational problems that cannot be studied using a steady state model alone (Ellul 2010).…”

Section: Introductionmentioning

confidence: 99%

Accelerated Dynamic Modeling for Complex Networks

Chidiac¹,

Sauvé²,

Pitts³

et al. 2015

Unconventional Resources Technology Conference

View full text Add to dashboard Cite

New developments in today's energy market have been trending towards large, complex production systems consisting of thousands of wells tied to one or more long trunklines; such developments include unconventional resources and geographically large-scale developments.During production, transient problems can occur in these complex systems that can have a negative impact on performance. These transient problems are best predicted and detected using transient multiphase flow simulator software. However, simulating these large complex networks in a transient simulator typically results in extended processing times. These large models often run slower than real-time and become impractical to use in online surveillance and monitoring applications or in forecasting scenarios. Engineers will not have enough time to react and mitigate the transient problems.To reduce the simulation time for these models, an integrated solution is required that captures the major transients of interest occurring in the complex networks while reducing the computational load. An integrated solution combines steady state and dynamic models building a representative asset model of the complex network.Breaking up the complex network into subnetworks where parts are solved with steady state simulators and others are solved with dynamic simulators is determined by observing the time constants of various parts of the network. The time constant is a measure of how quickly the system responds to changes in inputs. Selecting the time constant of interest determines the speed of solution. For all faster transients or smaller time constants, these subnetworks can be solved with steady state simulation. The subnetwork(s) of interest are modeled with a dynamic simulator.To combine the two simulation models into a single integrated asset model, boundary conditions between the transient and the steady state simulators should be in communication and synchronized at specific intervals to maintain the accuracy and fidelity of the overall model.Using an integrated solution for the simulation of large, complex networks can improve simulation time by an order of magnitude faster than a standalone transient simulation, while maintaining the accuracy of the results.This new integrated solution has proven to be very beneficial and practical for engineers since it allows fast, dynamic runs for complex networks, giving the user the ability to make timely decisions to mitigate operational problems and to run multiple, fast, sensitivity runs for different production scenarios.

show abstract

Section: Introductionmentioning

confidence: 99%

Accelerated Dynamic Modeling for Complex Networks

Chidiac¹,

Sauvé²,

Pitts³

et al. 2015

Unconventional Resources Technology Conference

View full text Add to dashboard Cite

show abstract

Accelerated Dynamic Modeling for Complex Networks

Chidiac

Sauvé

Pitts

et al. 2015

Proceedings of the 3rd Unconventional Resources Technology Conference

View full text Add to dashboard Cite

Data Analytics into Hydraulic Modelling for Better Understanding of Well/Surface Network Limits, Proactively Identify Challenges and, Provide Solutions for Improved System Performance in the Greater Burgan Field

Dashti

Matar

Abdulrazzaq

et al. 2021

Day 1 Mon, November 15, 2021

View full text Add to dashboard Cite

A network modeling campaign for 15 surface gathering centers involving more than 1800 completion strings has helped to lay out different risks on the existing surface pipeline network facility and improved the screening of different business and action plans for the South East Kuwait (SEK) asset of Kuwait Oil Company. Well and network hydraulic models were created and calibrated to support engineers from field development, planning, and operations teams in evaluating the hydraulics of the production system for the identification of flow assurance problems and system optimization opportunities. Steady-state hydraulic models allowed the analysis of the integrated wells and surface network under multiple operational scenarios, providing an important input to improve the planning and decision-making process. The focus of this study was not only in obtaining an accurate representation of the physical dimension of well and surface network elements, but also in creating a tool that includes standard analytical workflows able to evaluate wells and surface network behavior, thus useful to provide insightful predictive capability and answering the business needs on maintaining oil production and controlling unwanted fluids such as water and gas. For this reason, the model needs to be flexible enough in covering different network operating conditions. With the hydraulic models, the evaluation and diagnosis of the asset for operational problems at well and network level will be faster and more effective, providing reliable solutions in the short- and long-terms. The hydraulic models enable engineers to investigate multiple scenarios to identify constraints and improve the operations performance and the planning process in SEK, with a focus on optimal operational parameters to establish effective wells drawdown, evaluation of artificial lifting requirements, optimal well segregation on gathering centers headers, identification of flow assurance problems and supporting production forecasts to ensure effective production management.

show abstract

Online Asset Optimization Initiatives in Pemex Midstream

Cited by 4 publications

References 11 publications

Accelerated Dynamic Modeling for Complex Networks

Accelerated Dynamic Modeling for Complex Networks

Accelerated Dynamic Modeling for Complex Networks

Data Analytics into Hydraulic Modelling for Better Understanding of Well/Surface Network Limits, Proactively Identify Challenges and, Provide Solutions for Improved System Performance in the Greater Burgan Field

Contact Info

Product

Resources

About