Real Time Artificial Lift Timing and Selection Using Hybrid Data-Driven and Physics Models
Authors: Zalavadia Hardikkumar , Gokdemir Metin , Sinha Utkarsh , Singh Prithvi , Sankaran Sathish 
Published: May 2023

Abstract
Artificial lift is the backbone of unconventional field production. Lifting oil and gas in an optimal manner and economically is one of the most challenging phases of field development with depleting reservoir energy. Traditional approaches of lift selection are not sufficient to manage unconventional wells effectively, with high decline rates initially. It is of prime interest to understand production behavior under different lift conditions since the decision on timing and design of lift method are crucial for optimizing the well performance. This paper presents an artificial-lift timing and selection (ALTS) methodology based on a hybrid data-driven and physics-based workflow to maximize the value of unconventional oil and gas assets.
Our formulation employs a reduced physics model that is based on identification of Dynamic Drainage Volume (DDV) using commonly measured data (daily production rates and wellhead pressure) to calculate reservoir pressure depletion, transient productivity index (PI) and dynamic inflow performance relationship (IPR). Transient PI as the forecasting variable allows normalizing both surface pressure effects and considers phase behavior, thus reducing noise. The PI-based forecasting method is used to predict future IPRs and subsequently oil, water, and gas rates for any bottom hole pressure condition. The workflow allows estimating well deliverability under different artificial lift types and design parameters.
The ALTS workflow was applied to real field cases for wells flowing under different operating conditions to optimize the best strategy to produce the well amongst several candidate scenarios. Transient PI and dynamic IPR results provided valuable insights on how and when to select different AL systems. The workflow is run periodically with everchanging subsurface and wellbore conditions against each candidate scenario with various pump models and other operating parameters (pressure, speed etc.). The method was applied to several wells in a hindcasting mode to evaluate lost production opportunity and validate the results. In certain cases, the optimal recommendation pointed to selecting a different artificial lift system than the chosen method in the field to significantly improve long term well performance. In addition, optimal artificial lift operating point recommendations are made for wells including optimal gas lift rates for gas lifted wells, optimal pump unit selection and speed for wells on ESP and SRP.
The proposed method allows predicting future unconventional reservoir IPR consistently and has allowed continuous evaluation of artificial lift timing and selection scenarios for multiple lift types and designs in unconventional reservoirs. This can transform incumbent practices based on broad field heuristics, which are often ad hoc, inefficient, and manually intensive, towards well-specific ALTS analysis to improve field economics. Continuous application of this process is shown to improve production, reduce deferred production and increase life of lift equipment.