Improvement of the fast simulation of gamma-gamma density well logging measurement.

Approximation model Azimuthal density image Density well logging Fast simulation

Journal

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
ISSN: 1872-9800
Titre abrégé: Appl Radiat Isot
Pays: England
ID NLM: 9306253

Informations de publication

Date de publication:
Jan 2021
Historique:
received: 23 02 2020
revised: 24 08 2020
accepted: 10 09 2020
pubmed: 3 10 2020
medline: 3 10 2020
entrez: 2 10 2020
Statut: ppublish

Résumé

The fast modeling of gamma-gamma density well logging is essential for the inversion techniques of formation properties, which is usually carried out jointly with other logging measurements such as electrical logging. It also can help to adjust the initial geological model in real time during geosteering. The Monte Carlo method is the foremost numerical technique to simulate gamma-gamma density logging measurement. But due to its slow speed, it is not sufficient for inversion or real-time forward modeling. An algorithm to achieve the fast simulation of density logging response is introduced. In the algorithm, a new approximation model is proposed to enable accurate forward modeling of density logging with better efficiency. The Monte Carlo simulation method is utilized as a benchmark to validate the performance of the fast simulation method. The density logging responses under vertical and high-angle well conditions are simulated. The results of the fast simulation show a good agreement with the Monte Carlo simulations in vertical and high-angle wells. In addition, the comparison of density imaging data also confirmed the accuracy of the fast simulation method.

Identifiants

pubmed: 33007736
pii: S0969-8043(20)30569-8
doi: 10.1016/j.apradiso.2020.109423
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

109423

Informations de copyright

Copyright © 2020 Elsevier Ltd. All rights reserved.

Auteurs

Juntao Liu (J)

School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 730000, Gansu Province, China. Electronic address: liujuntao20082009@126.com.

Chao Yuan (C)

PetroChina Exploration and Production Company, PetroChina, Beijing, 100083, China.

Shanqing Cai (S)

School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 730000, Gansu Province, China.

Gang Chen (G)

Xi'an Science and Industry Group, China Coal Research Institute, Xi'an, 710000, Shanxi Province, China.

Heng Tian (H)

School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 730000, Gansu Province, China.

Zhiyi Liu (Z)

School of Nuclear Science and Technology, Lanzhou University, Lanzhou, 730000, Gansu Province, China. Electronic address: zhiyil@lzu.edu.cn.

Hong Zhou (H)

Department of Incident Evaluation and Experience Feedback, Nuclear and Radiation Safety Center, Beijing, 100082, China.

Classifications MeSH