Naturally Fractured Reservoirs: Evaluation, Characterization, and Simulation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (20 May 2022) | Viewed by 2524

Special Issue Editors

Lithica SCCL, Av. Farners 16, 17430 Sta Coloma de Farners, Spain
Interests: structural geology; characterization of fractured reservoirs; integration of subsurface; fieldwork and remote sensing data; outcrop analogues studies and virtual outcrop technologies
Equinor ASA, Sandsliveien 90, 5254 Sandsli Bergen, Norway
Interests: structural geology; characterization of fractured reservoirs; subsurface data integration
Shell Global Solutions International BV, Grasweg 31, 1031 HW Amsterdam, The Netherlands
Interests: faults fractures and fluid flow; deformation bands; machine learning; structural diagenesis; fault seal, seismic interpretation; digital rocks; microstructures and pores

Special Issue Information

Dear Colleagues,

Naturally fractured reservoirs are of great importance for hydrocarbons, water, CO2 storage and hydrothermal energy. Fractures control connectivity and permeability of these reservoirs and, thus, their characterization and thorough understanding are required for correct evaluation of business opportunities and planning of successful development strategies. Fracture data from subsurface reservoirs are often scattered and biased, forcing geoscientists to apply newer technologies and to integrate models derived from analogues in order to perform full field scale fracture characterization. The complexity of natural fracture networks, mostly related to a heterogeneous distribution of deformation, rock mechanical properties and diagenesis, represents a challenge for upscaling and simulation.

Dr. Giulio Casini
Dr. Ole Petter Wennberg
Dr. Antonino Cilona
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • naturally fractured reservoirs
  • evaluation
  • characterization
  • fluid flow simulation
  • modelling
  • upscaling
  • data integration
  • structural diagenesis
  • reservoir geomechanics
  • machine learning

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

13 pages, 25322 KiB  
Article
Adaptive Prediction of Enhanced Oil Recovery by N2 huff-n-puff in Fractured-Cavity Reservoir Using an FNN-FDS Hybrid Model
by Qi Wang, Hanqiao Jiang, Jianfa Han, Daigang Wang and Junjian Li
Appl. Sci. 2021, 11(19), 8871; https://0-doi-org.brum.beds.ac.uk/10.3390/app11198871 - 24 Sep 2021
Cited by 1 | Viewed by 1495
Abstract
N2 huff-n-puff has proven to be a promising technique to further improve oil recovery in naturally fractured-cavity carbonate reservoirs. The effect of enhanced oil recovery (EOR) by N2 huff-n-puff is significantly affected by various dynamic and static factors such as type [...] Read more.
N2 huff-n-puff has proven to be a promising technique to further improve oil recovery in naturally fractured-cavity carbonate reservoirs. The effect of enhanced oil recovery (EOR) by N2 huff-n-puff is significantly affected by various dynamic and static factors such as type of reservoir space, reservoir connectivity, water influx, operational parameters, and so on, typically leading to a significant increase in oil production. To reduce the prediction uncertainty of EOR performance by N2 huff-n-puff, an adaptive hybrid model was proposed based on the fundamental principles of fuzzy neural network (FNN) and fractional differential simulation (FDS); a detailed prediction process of the hybrid model was also illustrated. The accuracy of the proposed FNN-FDS hybrid model was validated using production history of N2 huff-n-puff in a typical fractured-cavity carbonate reservoir. The proposed model was also employed to predict the EOR performance by N2 huff-n-puff in a naturally fractured-cavity carbonate reservoir. The methodology can serve as an effective tool to optimize developmental design schemes when using N2 huff-n-puff to tap more remaining oil in similar types of carbonate reservoirs. Full article
Show Figures

Figure 1

Back to TopTop