Content Tagged: "reservoir surveillance"

Acquire and analyze the necessary data for optimizing reservoir surveillance. Upon completion of this module, the participant should be able to acquire and analyze pressure data, PVT reports, production records, injection records, production tests, fluid sampling, injectivity tests, and other information for the purpose of monitoring reservoir behavior.

Optimize reservoir management and control decisions using surveillance techniques, information systems, technical indicators and financial guidelines. Upon completion of this module, the participant should be able to do the following: manage available resources (e.g., reserves, assets, personnel, budget) in order to maximize hydrocarbon reserves and minimize recovery cost and make appropriate reservoir management and control decisions with the aid of surveillance techniques, information systems and technology applications to generate pressure and production histories, maps and other key reservoir data.

Understand and apply reservoir surveillance and control techniques to confirm the materialization of the proposed strategies in the reservoir exploitation scheme. Upon completion of this module, the participant should be able to compare actual reservoir behavior to various performance prediction tools and account for differences, evaluate the effectiveness of the exploitation strategy, and explain reasons why actual reservoir performance deviated from initial predictions.

This webinar focuses on how to present surveillance results to a multi-disciplinary team and/or management in a way that decisions can be made correctly and quickly.

The oil industry has a great experience with the applications of Data Analytics/ Artificial Intelligence/ Machine Learning (DA/AI/ML) in the Reservoir

Watch Chris Fair provide a preview of paper 210159 being presented at ATCE 2022

The digital transformation brought about by edge computing, real-time surveillance, and high-speed interpretation has reduced reaction times, increase

This webinar will cover how physics and data-driven methods can be merged in practical ways for automating reservoir surveillance with applications to pressure transient analysis.

In this presentation, the speaker will briefly review the status of tracer technology, present recent improvements and highlight case studies that apply these methodologies.

This presentation will outline the theory of cross-well EM system, survey design and modelling, data acquisition configuration and workflow. Two field examples will be presented to demonstrate the usefulness of the method for fluid monitoring, reservoir characterization and locate by-passed hydrocarbon.

This webinar will begin with some fundamentals of streamline simulation and surveillance. We will also discuss the minimum amount of data needed to build a surveillance model and how to interpret novel streamline-based surveillance metrics. Lastly, we will show that by knowing well-pair connections and pattern efficiencies, this provides the basis of a simple flood optimization via updated well rate targets.