Unconventional field production heavily relies on artificial lift, but with reservoir energy depleting, efficiently and economically lifting oil and gas is one of the most difficult aspects of field development. For unconventional wells with high initial decline rates, traditional lift selection methods are often ad hoc and suboptimal. Understanding how production behaves under various lift conditions is critical because the most important considerations for optimizing well performance are lift method selection, timing, and design. In this work, we present a hybrid data-driven and physics-based workflow to optimize artificial-lift timing and selection (ALTS) and operations to increase the value of unconventional oil and gas assets.
Our formulation uses commonly measured data (flowback, daily production rates, and wellhead pressure and PVT) to develop a data-driven model rooted in physics-based principles and estimate well deliverability with varying artificial lift types in a computationally efficient manner. The idea is rooted in the concept of Dynamic Drainage Volume (DDV) to calculate reservoir pressure depletion, transient productivity index (PI) and dynamic inflow performance relationship (IPR). Transient PI as the forecasting variable normalizes both surface pressure effects and takes phase behavior into account, reducing noise. The PI-based forecasting method is used to predict future IPRs and, as a result, oil, water, and gas rates for any bottom hole pressure or operating condition.
Transient PI and dynamic IPR offered insightful guidance on how and when to choose various AL systems on actual field cases. Various pump models and operating parameters are used to run the workflow regularly with constantly changing subsurface and wellbore conditions against each candidate scenario (wellhead pressures, pump speed etc.). For assessing missed production opportunities and validating the findings, the method was applied in hindcasting mode to several wells. In some instances, alternate optimal lift systems were proposed to significantly enhance long-term well performance. Additionally, optimal artificial lift operating point recommendations for wells are made, including optimal gas lift rates for gas lifted wells, optimal pump unit selection and speed for ESP and SRP wells.
The proposed technique provides a systematic and field-scale method to predict future unconventional reservoir IPR consistently that allows for continuous evaluation of artificial lift timing and selection scenarios with multiple lift types and designs. The workflow was applied to wells flowing under various operating conditions to choose the best approach for producing the well from a list of potential lift options. The proposed workflow might lead to a change in way from current techniques based on broad field heuristics, which are typically ad hoc, ineffective, suboptimal, and labor-intensive, towards more robust, optimal, and well-specific ALTS analysis in a timely manner. It has been demonstrated that ongoing usage of this procedure increases production, reduces deferred production, and increases the lifespan of lift equipment.
