Research on Nuclear Magnetic Resonance Logging Inversion Method and Application

DOI

10.2991/978-94-6463-415-0_31How to use a DOI?

Keywords

Nuclear magnetic resonance logging; Reservoir parameter evaluation; Capillary pressure curve prediction; Inversion; Microdistribution of fluids

Abstract

uclear magnetic resonance logging is an effective means of reservoir evaluation and has been widely used in oil and gas resources exploration and development. The traditional nuclear magnetic resonance logging application requires the inversion of the echo data first to get the inversion spectrum, from which then the required formation information is extracted. The evaluation of reservoir parameters, the prediction of capillary pressure curve and the microdistribution of reservoir constraints and dynamic fluid are the three important aspects of nuclear magnetic resonance logging application. The existing application of nuclear magnetic resonance logging faces serious problems. In this paper, three methods of time-domain analysis are proposed, and the echo data is not required to be invert to get the horizontal relaxation time (t2) spectrum. The influence of inversion on the evaluation of the water saturation and permeability evaluation is avoided. Methods 1 is the reservoir irreducible water saturation and permeability evaluation method based on echo data calibration. Method 2 is the reservoir of water saturation and permeability evaluation method based on the index hyperbola sinusoidal transformation. Method 3 is the reservoir permeability evaluation method based on the variable time domain characteristics parameter. Based on the prediction of the capillary pressure curve, this paper puts forward the prediction method of the capillary pressure curve based on the integral transformation-quantum genetic-neural network. The results of core rock experiment and nuclear magnetic resonance logging data showed that compared with the traditional nonlinear regression method, integral transformation, the traditional nonlinear regression method and the integral transformation, the integral transformation-the quantum genetic neural network method was the best method to predict the optimal effect of the capillary pressure curve.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Juntao Wang
AU  - Jie Wu
AU  - Ni Nie
PY  - 2024
DA  - 2024/05/14
TI  - Research on Nuclear Magnetic Resonance Logging Inversion Method and Application
BT  - Proceedings of the 2023 9th International Conference on Advances in Energy Resources and Environment Engineering (ICAESEE 2023)
PB  - Atlantis Press
SP  - 299
EP  - 306
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-415-0_31
DO  - 10.2991/978-94-6463-415-0_31
ID  - Wang2024
ER  -