Waterflooding Performance Predictions and Surveillance
Premium Workshop
For PEA Members Only
This workshop explores methods for predicting and monitoring waterflood performance to improve recovery efficiency and reservoir management. Participants will gain practical knowledge of surveillance techniques, performance analysis, and strategies for optimizing waterflood operations.
Workshop Objectives
Understand the principles of waterflooding and recovery mechanisms.
Learn techniques for predicting waterflood performance.
Apply surveillance methods to monitor and evaluate injection and production.
Use analysis results to optimize recovery and support reservoir management decisions.
About the Presenter
The presenter is an experienced professional with expertise in reservoir engineering, enhanced oil recovery, and production optimization. With a blend of technical knowledge and practical field experience, the presenter offers valuable insights to strengthen participants’ capabilities in waterflood management.
Premium Workshop
For PEA Members Only
Modern Reservoir Characterization : Integrating Artificial Intelligence (AI) with Traditional Methods
During this workshop, participants will develop a more comprehensive grasp of the geophysical theory of seismic inversion and explore advanced seismic reservoir characterization techniques. Discover the essential steps in the seismic reservoir characterization workflow using machine learning, covering data processing to inversion analysis. Acquire valuable knowledge applicable to your everyday projects.In classical reservoir characterization, it is commonly assumed that the reservoir exhibits both elastic and hydraulic isotropy. However, real reservoirs often exhibit anisotropic characteristics and spatial heterogeneity on multiple scales. Relying solely on core and log data may not accurately represent the larger reservoir volume. Therefore, the most effective way to accurately analyze the physical properties of most actual reservoirs, across their entire volume, involves utilizing advanced machine learning methods for acquired and interpreted seismic data.