Establishing Time-Depth Relationships Constrained by Modes of the Reservoir Architecture
PDF

Keywords

Wavelet
Reservoir
Seismic well tie
Architecture mode
Time-depth relationship

How to Cite

1.
Fang H, Yang S, Zhang G, Xu H. Establishing Time-Depth Relationships Constrained by Modes of the Reservoir Architecture. Int. J. Petrol. Technol. [Internet]. 2022 Apr. 15 [cited 2022 Aug. 13];9:1-7. Available from: https://avantipublishers.com/index.php/ijpt/article/view/1207

Abstract

Time-depth relationships (TDRs) can connect seismic and wireline logs, both essential characterization data of reservoirs. The seismic well tie is always a complex work on account of the complicated reservoir structures. Since seismic and logging data are responses of reservoir architectures, the seismic well tie can be efficiently improved constrained by the reservoir architectures. This study adopts a clastic reservoir as the study area. Three architecture modes (i.e., normal cycle mode, inverse-normal cycle mode, and homogeneous-normal cycle mode) are summarized based on combinations of architecture elements. For the generation of the synthetic seismograms, optimized wavelets (i.e., wavelet A, wavelet B, and wavelet C) are suitable for the wells belonging to normal cycle mode, inverse-normal cycle mode, and homogeneous-normal cycle mode, respectively. Precise TDRs are established by matching the synthetics and seismic traces. Wells belong to the same architecture mode and have similar TDRs. The two-way travel time is shortest in the same depth interval of homogeneous-normal cycle mode compared to other architecture modes.

https://doi.org/10.54653/2409-787X.2022.09.1
PDF

References

Wagoner J, Mitchum R, Campion K, Rahmanian V. Siliciclastic sequence stratigraphy in well logs, cores, and outcrops: concepts for high-resolution correlation of time and facies. AAPG Special Volumes, 1990; 3-55. https://doi.org/10.1306/Mth7510

Wu X, Shi Y, Fomel S. Incremental correlation of multiple well logs following geologically optimal neighbors. Interpretation, 2018; 6(3): T713-T722. https://doi.org/10.1190/INT-2018-0020.1

Li W, Yue D, Colombera L, Wu S. A novel method for estimating sandbody compaction in fluvial successions. Sedimentary Geology, 2020; 404. https://doi.org/10.1016/j.sedgeo.2020.105675

Bi Z, Wu X, Li Y, Yan S, Zhang S, Si H. Geological-time-based interpolation of borehole data for building high-resolution models: methods and applications. Geophysics, 2022; 87(3): A165-A176. https://doi.org/10.1190/geo2021-0340.1

Smith T, Waterman M. New stratigraphic correlation techniques. The Journal of Geology, 1980; 451-457. https://doi.org/10.1086/628528

Scott W, Leaney P, Ulrych T. Multiple dynamic matching: a new approach to well log correlation[J]. Geoexploration, 1987; 24(6): 503-515. https://doi.org/10.1016/0016-7142(87)90018-4

Wheeler L, Dave H. Simultaneous correlation of multiple well logs. Society of Exploration Geophysicists International Exposition and 84th Annual Meeting SEG, 2014; 618-622. https://doi.org/10.1190/segam2014-0227.1

Muñoz A, Dave H. Automatic simultaneous multiple well ties. Geophysics, 2015; 80(5): IM45-IM51. https://doi.org/10.1190/geo2014-0449.1

Herrera R, Baan M. A semiautomatic method to tie well logs to seismic data. Geophysics, 2014; 79(3): V47-V54. https://doi.org/10.1190/geo2013-0248.1

Cubizolle F, Valding T, Lacaze S, Pauget F. Global method for seismic-well tie based on real time synthetic model. SEG Technical Program Expanded Abstracts, 2015. https://doi.org/10.1190/segam2015-5862834.1

Zhang B, Yang Y, Pan Y, Wu H, Cao D. Seismic well tie by aligning impedance log with inverted impedance from seismic data. Interpretation, 2020; 8: T917-T925. https://doi.org/10.1190/INT-2019-0289.1

Wu H, Li Z, Liu N, Zhang B. Improved seismic well tie by integrating variable-size window resampling with well-tie net. Journal of Petroleum Science and Engineering, 2022; 208. https://doi.org/10.1016/j.petrol.2021.109368

Hornby B, Howie J, Ince D. Anisotropy correction for deviated-well sonic logs: Application to seismic well tie. Geophysics, 2003; 68(2): 464-471. https://doi.org/10.1190/1.1567212

Behiry M, Araby M, Ragab R. Impact of phase rotation on reservoir characterization and implementation of seismic well tie technique for calibration offshore Nile Delta, Egypt. The leading edge, 2022; 39: 346-352. https://doi.org/10.1190/tle39050346.1

Bosch M, Mukerji T, Gonzalez E. Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review. Geophysics, 2010; 75(5): 1-53. https://doi.org/10.1190/1.3478209

Shahin A, Tatham R, Stoffa P, Spikes K. Optimal dynamic rock-fluid physics template validated by petroelastic reservoir modeling. Geophysics, 2011; 76(6): O45-O58. https://doi.org/10.1190/geo2010-0275.1

Liu H, Xia Q, Zhou X. Geologic-seismic models, prediction of shallow water lacustrine delta sandbody and hydrocarbon potential in the Late Miocene, Huanghekou Sag, Bohai Bay Basin, northern China. Journal of Palaeogeography, 2018; 7(1): 66-87. https://doi.org/10.1016/j.jop.2017.11.001

Wang M, Xie J, Zhang Q, Duan Y. Characteristics and sedimentary model of a reticular shallow water delta with distributary channels: lower member of the Neogene Minghuazhen Formation in the Bozhong area of the Huanghekou Sag, China. Arabian Journal of Geosciences, 2019; 12(24): 1-21. https://doi.org/10.1007/s12517-019-4928-5

Tian L, Niu C, Du X, Yang B, Lan X, Chen D. Development characteristics and controlling factor analysis of the Neogene Minghuazhen Formation shallow water delta in Huanghekou area. Journal of Paleogeography, 2019; 8(19): 1-19. https://doi.org/10.1186/s42501-019-0032-8

Hao S, Liu H, Du X, Niu C, Sedimentary characteristics of shallow-water delta and responses features in palaeoenvironment: a case study from the lower part of Neogene Minghuazhen Formation. Arabian Journal of Geosciences, 2020; 14: 1-16. https://doi.org/10.1007/s12517-021-06572-y

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2022 Huijing Fang, Shubo Yang, Guocan Zhang, Huaimin Xu