Development of a Multi-method Dynamic Simulation Model: Exploring Opportunities for Produced Water Reuse

Published Date:

March 2021


Saeed P. Langarudi, Robert P. Sabie, Babak Bahaddin, Alexander G. Fernald


This report explores the possibility and plausibility of developing a hybrid simulation method combining agent-based (AB) and system dynamics (SD) modeling to address produced water management (PWM) issues. We start by developing a conceptual diagram to capture the extent and scale of the complexity of a PWM model. We use literature, information characterizing produced water in New Mexico, and our preliminary interviews with subject matter experts to develop this framework. We then conduct a systematic literature review to summarize state-of-the-art of hybrid modeling methodologies and techniques. Our research reveals there is a small but growing volume of hybrid modeling efforts that could provide some foundational support for PWM modelers. We categorize these efforts in four classes based on their approach to hybrid modeling. Class A includes models with two separate sets of AB and SD modules that work independently but talk to each other through a protocol. Class B includes models with AB modules that directly contain SD (stock, flow, and feedback) structures. Class C includes models with SD modules that directly contain AB (heterogenous behavioral rules and agent interaction) structures. Class D includes the most sophisticated hybrid AB-SD models that fully integrate both approaches where AB modules contain SD structures and SD modules contain AB structures and simultaneously there is a seamless communication at the aggregate level between AB and SD modules. It appears that, among these classes, PWM requires the most sophisticated approach (Class D), indicating that PWM modelers will need to face serious challenges of breaking new ground in this realm. The report concludes with an outline for future research.


Technical Report 391

Produced Water Management, Hybrid Modeling, Simulation, System Dynamics, Agent-based Modeling, Geospatial Analysis, Cross-scale Complexity