... Abstract A framework that integrates an AI surrogate with a carbon accounting simulator to optimize well locations and control strategies in subsurface flow operations is presented in this paper. The primary objective is to maximize Net Present Value (NPV) by balancing operational efficiency...

... Abstract Reinforcement learning (RL) has gained interest in chemical process and production industries for control and optimization of the process. The RL algorithm does not need any kind of field knowledge to start the optimization process. The algorithm will be trained and adjusted during...

... Abstract The design, operation, and optimization of Sucker Rod Pumping (SRP) systems necessitate the utilization of production data. However, forecasting fluid flow rates at the surface of SRP artificially lifted wells usually poses a challenge, especially in instances where traditional...

... Summary The objective is to demonstrate an optimal well design for a potential geological carbon storage (GCS) project. CO 2 plume shape, size, and pressure response in the subsurface are design variables. The chosen well trajectory improves injectivity while minimizing formation pressure...

... Abstract Well intervention for restoring or increasing production is a routine activity in any oilfield, however, it becomes an optimization opportunity for large fields with thousands of wells and high failure rate. Balancing between proactive and reactive workovers to optimize the rig...

... Abstract Well placement optimization is a complicated problem which is usually solved by direct combination of reservoir simulators with optimization algorithm. However, depending on complexity of the reservoir model studied, thousands of simulations is usually needed for accurate and reliable...

... Abstract Field-scale simultaneous optimization of well rate and polymer concentration is challenging due to the geologic heterogeneity, large number of wells, and operational constraints. This paper proposes a multi-stage optimization strategy to achieve a multi-objective goal: maximize...

... Abstract Modeling the drill bit Rate of Penetration (ROP) is crucial for optimizing drilling operations as maximum ROP causes fast drilling, reflecting efficient rig performance and productivity. In this paper, four Ensemble machine learning (ML) algorithms were adopted to reconstruct ROP...

... Abstract Optimization of production networks is key for managing efficient hydrocarbon production as part of closed-loop asset management. Large-scale surface network optimization is a challenging task that involves high nonlinearity with numerous constraints. In existing tools...

... Abstract This paper presents a methodology for the identification of a dynamic-surrogate model and the optimization of steam injection rates of a multi-well heterogeneous SAGD process. The optimization refers to finding the steam injection rates at every time step (steam injection policy...

... in the industry applied model approaches. production monitoring upstream oil & gas reservoir pressure pressure loss reservoir surveillance drillstem/well testing pressure drop fracture half-length hydraulic fracturing reservoir system optimization drainage radius production control drainage...

... and stress changes around parent wells, landing strategy, completion optimization, frac order design, etc. A 3-D reservoir model was developed to estimate the depletion and the induced stress changes around the parent wells. Hydraulic fracture modeling is coupled with the flow simulation model to assess...

... Abstract The rate of penetration (ROP) was optimized using a particle swarm optimization algorithm for real-time field data to reduce drilling time and increase efficiency. ROP is directly related to drilling costs and is a major factor in determining mechanical specific energy, which is often...

... calculation water saturation producer algorithm geology data optimization workflow aquifer Artificial Intelligence Thickness water movement saturation map surveillance equation Reservoir Characterization modeling information waterflood production history saturation Introduction...

... Abstract In this work, we present and apply a comprehensive prescriptive analytics framework for well completion optimization in unconventional resources. The methodology involves 1) data processing, ingestion into databases, and data cleansing 2) application of AutoML for generating...

... Abstract Steam-assisted Gravity Drainage (SAGD) is one of the major thermal recovery methods for heavy oil. Optimization of SAGD is a delicate process that needs to be planned and operated in a detailed manner. Steam trapping is one of the methods that may help optimize production in SAGD...

... matrix Salehi equation compartment Jacobian matrix sequence transmissibility reservoir permeability reservoir simulation optimization algorithm Durlofsky compartmentalized reservoir non-local formulation Introduction In subsurface flow modeling, subsurface formations...

... In general, the high cost of drilling, coupled with the limited information at the early stages of the project, results in a strategy to delay drilling decisions until more information about the reservoir is acquired. Therefore, optimization techniques should always consider the possibility...

... optimization average reservoir pressure reservoir artificial neural network dynamic layered pressure map generation neural network pressure data falloff test synthetic data operation Introduction The objective of this work is to present a methodology which provides actionable and confident...

..., and/or political considerations. The interests of these stakeholders may be potentially in conflict with each other, entailing that a robust development plan should take into account all these concerns. Multiobjective optimization (MOO) can be used to find a set of optimal solutions (i.e., the so-called Pareto...