SWS Academic Research eLibraryEarth & Planetary Sciences

Scholarly record

PREDICTION RESERVOIRS BASED ON THE RESULTS OF PETRO-ELASTIC MODELING

Ildar Sakhautdinov

First published: 2018-06-20https://doi.org/10.5593/sgem2018/1.4/s06.090View metrics

Abstract

Recently, Russian oil companies in oil fields are working on clarifying the "old" and identifying new geological structures discovered by the results of seismic exploration. This is due to the fact that oil reserves in both clastic and carbonate rocks with high and medium porosity have almost completely been developed. To clarify the "new" geological structures and revaluation of oil reserves, seismic models are being built. Modeling of elastic rock properties (Rock Physics) allows to link their reservoir properties, estimated from the indications of geophysical methods, to their seismic field. The results of such modeling allow to evaluate the possibilities of various types of seismic inversion and are the basis for prediction "new" productive deposits in old deposits. To clarify the geological structure of the oil reservoir, the results of recording the physical properties of the oilfield section in all wells are needed. Unfortunately, in the old wells, well logging are performed by an incomplete set of methods: no data of density, acoustic logging and resistivity logging. Either the registration of these parameters was performed only partially, in separate intervals of depth along the well section. Today, various methods are used to restore the physical properties of the well section, such as acoustic properties and density. These include the methods of Faust, Gardner, Casta?a, Zaliaev, etc. [1], [2], [3], [4]. All these methods relate to each other the elastic properties of the formation and its physical parameters. But in the context of an incomplete set of well logging data, their application is either very limited or not possible at all. As a rule, a set of well logging data always include the recording of neutron log (NC) and gamma-ray logging (GR). This means that there is always information on the porosity and clayiness of the oilfield. In this paper, it is shown that the elastic properties of rocks can be reconstructed from the results of calculating porosity by the example of oil fields in the Volga-Ural province of Russia. Geological researches of oilfields and well logging are carried out for the quantitative description of the reservoir. In other words, to create a reliable volumetric reservoir model based on the results of seismic exploration and well logging, which describes the distribution of its petrophysical properties such as lithology, porosity, permeability, saturation, etc. Analysis of the elastic properties of rocks can determine the relationship between petrophysical parameters and seismic data, and stable relationships are the basis for building a petro-elastic reservoir model. This work is devoted, firstly, to solving the problems of correction and reconstructing the acoustic log data and density, necessary for seismostratigraphic binding of the wave field and seismic pulse generation and, secondly, for constructing a petro-elastic model for estimating the possibility of seismic inversion and reservoir prediction in the interwell space. The model of elastic properties of clastic rocks is obtained in two ways on the basis of well logging data analysis. Comparison of the elastic properties of the prediction results is performed. A good convergence of synthetic acoustic and density logs calculated by the component method was obtained.

Publication Impact Profile

PlumX
  • Citations
  • Scopus - Citation Indexes: 1
  • Captures
  • Mendeley - Readers: 1

Publication details

Title
PREDICTION RESERVOIRS BASED ON THE RESULTS OF PETRO-ELASTIC MODELING
Authors
Ildar Sakhautdinov
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 18th International Multidisciplinary Scientific GeoConference SGEM2018, Science and Technologies in Geology, Exploration and Mining
Publisher
STEF92 Technology
Year
2018
Pages
689-696
SWS Citekey
Sakhautdinov20186689696
ISSN
1314-2704
ISBN
978-619-7408-38-6
Language
en
Publication type
Conference Paper
Proceedings contents
Open official contents
Keywords
References0
0references registered for this publication

Structured references will appear here after the reference import pass. The count is preserved now so the scholarly record is not incomplete.

View or Download full articleAccess options
Full paper accessChoose SWS login, librarian support, or instant article download.

SWS access login

Login as SWS Scientific Committee

Authors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.

For librarian assistance: [email protected]

Purchase Instant Access

48-hour online accessComing soon
Online-only accessComing soon
Download the full article in PDF formatEUR 35
  • Article can be downloaded after successful payment.
  • Article may be used according to SWS library access terms.
  • Article cannot be redistributed.
Get full paper

Back to publication list