Coupling a cloud-based reservoir simulator and near wellbore modelling software for inorganic scale risk management

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work presents a way how the water production and injection profiles extracted from the full field reservoir simulation model may then be used as input for near wellbore squeeze treatment calculations, such as those performed using a squeeze model, to calculate inhibitor displacement, retention in the reservoir and then flow back into the wells, so that inhibitor returns and squeeze lifetimes can be calculated. An advantage of the simulator being available in the cloud is that it allowed the authors to perform the required calculations in a short timeframe using only the resources required, thus increasing efficiency of the evaluation and management of the inorganic scale risk. Integration of cloud-based reservoir simulator with the squeeze modelling package enabled not only an identification of the probable extent of the scaling problem, and also paved a path to optimising the design of squeeze treatments. Coupling of software combines the best estimate of water production rates and profiles available to the reservoir engineering team with placement calculations, and thus represents the best estimate of the well performance that can be updated on regular basis and integrated with a concept of a “digital field”.

Original languageEnglish
Title of host publication81st EAGE Conference and Exhibition 2019
PublisherEAGE Publishing BV
ISBN (Electronic)9789462822894
Publication statusPublished - 3 Jun 2019
Event81st EAGE Conference and Exhibition 2019 - London, United Kingdom
Duration: 3 Jun 20196 Jun 2019

Conference

Conference81st EAGE Conference and Exhibition 2019
CountryUnited Kingdom
CityLondon
Period3/06/196/06/19

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics

Fingerprint Dive into the research topics of 'Coupling a cloud-based reservoir simulator and near wellbore modelling software for inorganic scale risk management'. Together they form a unique fingerprint.

Cite this