Analysis of reservoir heterogeneities and depositional environments: a new method
Cyril D. Boateng 1 2 Li-Yun Fu 1 31 Key Laboratory of Petroleum Resource Research, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China.
2 University of Chinese Academy of Sciences, Beijing 100049, China.
3 Corresponding author. Email: lfu@mail.iggcas.ac.cn
Exploration Geophysics 49(6) 868-880 https://doi.org/10.1071/EG17072
Submitted: 12 January 2017 Accepted: 8 January 2018 Published: 22 February 2018
Abstract
A new methodology is presented to quantify reservoir heterogeneities based on a Monte Carlo parameter estimation technique from sonic logs. The acoustic reservoir heterogeneities are then quantified as an indicator to differentiate depositional environments and reservoir facies for geological interpretation in this study. Fractal statistics provides us with a framework to model reservoir heterogeneities with different Hurst numbers, correlation lengths and fluctuation standard deviations from sonic logs. These fractal parameters are derived from the von Karman autocorrelation model and estimated by an improved methodology using a Monte Carlo parameter estimation technique. Unlike the regular estimation method, the Monte Carlo parameter estimation technique is more stable. The resulting Hurst numbers, correlation lengths and root mean square (RMS) heights from 20 sonic logs are mapped in a reservoir with sandstone–mudstone sequences over complex continental deposits in north-eastern China. The spatial distribution of estimated reservoir heterogeneity parameters are then correlated with depositional facies interpretation derived from seismic attributes and petrophysical properties based on prior geological knowledge. Numerical experiments show that the Monte Carlo parameter estimation technique is successful in recovering acoustic heterogeneity parameters from sonic logs. Results from qualitative correlational analysis of sonic logs from the complex continent deposits in north-eastern China show that these parameters can be key discriminants for depositional facies and environments and may be utilised as a constraint in reservoir characterisation. Maps of Hurst numbers and correlation lengths strongly correspond with reservoir facies distributions, whereas maps of RMS heights correlate significantly with fluvial depositional patterns. The results were generally uniform even when different depth ranges within the formation of interest were used as input for parameter estimation. Numerical values of reservoir heterogeneity parameters may not fully recover the geology of a given reservoir but their distribution in space is an important indication of the morphological features of depositional environments.
Key words: depositional environments, fractals, Monte Carlo technique, morphological features, reservoir heterogeneities, sonic logs, von Karman autocorrelation model.
References
Allen, M. B., Macdonald, D. I. M., Xun, Z., Vincent, S. J., and Brouet-Menzies, C., 1997, Early Cenozoic two-phase extension and late Cenozoic thermal subsidence and inversion of the Bohai Basin, northern China: Marine and Petroleum Geology, 14, 951–972| Early Cenozoic two-phase extension and late Cenozoic thermal subsidence and inversion of the Bohai Basin, northern China:Crossref | GoogleScholarGoogle Scholar |
Bendat, J. S., and Piersol, A. G., 2010, Random data: analysis and measurement procedures: John Wiley & Sons, Inc.
Browaeys, T., and Fomel, S., 2009, Fractal heterogeneities in sonic logs and low-frequency scattering attenuation: Geophysics, 74, WA77–WA92
| Fractal heterogeneities in sonic logs and low-frequency scattering attenuation:Crossref | GoogleScholarGoogle Scholar |
Dimri, V. P., 2005, Fractals in geophysics and seismology: an introduction, in V. P. Dimri, ed., Fractal behaviour of the earth system: Springer, 1–19.
Dolan, S., Bean, C., and Riollet, B., 1998, The broad-band fractal nature of heterogeneity in the upper crust from petrophysical logs: Geophysical Journal International, 132, 489–507
| The broad-band fractal nature of heterogeneity in the upper crust from petrophysical logs:Crossref | GoogleScholarGoogle Scholar |
Ellis, D. V., and Singer, J. M., 2007, Well logging for earth scientists: Springer.
Frankel, A., and Clayton, R. W., 1984, Finite-difference simulation of wave propagation in two-dimensional random media: Bulletin of the Seismological Society of America, 74, 2167–2186
Frankel, A., and Clayton, R. W., 1986, Finite difference simulations of seismic scattering: implications for the propagation of short-period seismic waves in the crust and models of crustal heterogeneity: Journal of Geophysical Research: Solid Earth, 91, 6465–6489
| Finite difference simulations of seismic scattering: implications for the propagation of short-period seismic waves in the crust and models of crustal heterogeneity:Crossref | GoogleScholarGoogle Scholar |
Fu, L.-Y., Wu, R.-S., and Campillo, M., 2002, Energy partition and attenuation of regional phases by random free surface: Bulletin of the Seismological Society of America, 92, 1992–2007
| Energy partition and attenuation of regional phases by random free surface:Crossref | GoogleScholarGoogle Scholar |
Goff, J. A., and Jordan, T. H., 1988, Stochastic modeling of seafloor morphology: inversion of sea beam data for second-order statistics: Journal of Geophysical Research: Solid Earth, 93, 13589–13608
| Stochastic modeling of seafloor morphology: inversion of sea beam data for second-order statistics:Crossref | GoogleScholarGoogle Scholar |
Holliger, K., 1996, Upper-crustal seismic velocity heterogeneity as derived from a variety of P-wave sonic logs: Geophysical Journal International, 125, 813–829
| Upper-crustal seismic velocity heterogeneity as derived from a variety of P-wave sonic logs:Crossref | GoogleScholarGoogle Scholar |
Holliger, K., and Levander, A., 1994, Structure and seismic response of extended continental crust: stochastic analysis of the Strona-Ceneri and Ivrea zones, Italy: Geology, 22, 79–82
| Structure and seismic response of extended continental crust: stochastic analysis of the Strona-Ceneri and Ivrea zones, Italy:Crossref | GoogleScholarGoogle Scholar |
Holliger, K., Green, A. G., and Juhlin, C., 1996, Stochastic analysis of sonic logs from the upper crystalline crust: methodology: Tectonophysics, 264, 341–356
| Stochastic analysis of sonic logs from the upper crystalline crust: methodology:Crossref | GoogleScholarGoogle Scholar |
Hu, J., Xu, S., Xiaoguang, T., and Wu, H., 1989, The Bohai Basin, in X. Zhu, ed., Chinese sedimentary basins: Elsevier, 89–105.
Ikelle, L. T., Yung, S. K., and Daube, F., 1993, 2-D random media with ellipsoidal autocorrelation functions: Geophysics, 58, 1359–1372
| 2-D random media with ellipsoidal autocorrelation functions:Crossref | GoogleScholarGoogle Scholar |
Jarzyna, J. A., Bala, M. J., Mortimer, Z. M., and Puskarczyk, E., 2013, Reservoir parameter classification of a Miocene formation using a fractal approach to well logging, porosimetry and nuclear magnetic resonance: Geophysical Prospecting, 61, 1006–1021
| Reservoir parameter classification of a Miocene formation using a fractal approach to well logging, porosimetry and nuclear magnetic resonance:Crossref | GoogleScholarGoogle Scholar |
Kennedy, M., 2015, Introduction to log analysis: Shale volume and parameter picking, in M. Kennedy, ed., Developments in petroleum science: Elsevier, 151–180.
Liu, J., and Marfurt, K., 2007, Multicolor display of spectral attributes: The Leading Edge, 26, 268–271
| Multicolor display of spectral attributes:Crossref | GoogleScholarGoogle Scholar |
López, M., and Aldana, M., 2007, Facies recognition using wavelet based fractal analysis and waveform classifier at the Oritupano-A Field, Venezuela: Nonlinear Processes in Geophysics, 14, 325–335
| Facies recognition using wavelet based fractal analysis and waveform classifier at the Oritupano-A Field, Venezuela:Crossref | GoogleScholarGoogle Scholar |
Mandelbrot, B., 1982, The fractal geometry of nature: Macmillan.
Miall, A., 2014, Fluvial depositional systems: Springer International.
O’Doherty, R. F., and Anstey, N. A., 1971, Reflections on amplitudes: Geophysical Prospecting, 19, 430–458
| Reflections on amplitudes:Crossref | GoogleScholarGoogle Scholar |
Painter, S., and Paterson, L., 1994, Fractional Lévy motion as a model for spatial variability in sedimentary rock: Geophysical Research Letters, 21, 2857–2860
| Fractional Lévy motion as a model for spatial variability in sedimentary rock:Crossref | GoogleScholarGoogle Scholar |
Partyka, G., Gridley, J., and Lopez, J., 1999, Interpretational applications of spectral decomposition in reservoir characterization: The Leading Edge, 18, 353–360
| Interpretational applications of spectral decomposition in reservoir characterization:Crossref | GoogleScholarGoogle Scholar |
Qiao, B., Liu, S., Zeng, H., Li, X., and Dai, B., 2015, Limitation of the least square method in the evaluation of dimension of fractal Brownian motions: ArXiv:1507.03250, 1–7.
Roth, M., and Korn, M., 1993, Single scattering theory versus numerical modeling in 2D random media: Geophysical Journal International, 112, 124–140
| Single scattering theory versus numerical modeling in 2D random media:Crossref | GoogleScholarGoogle Scholar |
Ryder, R. T., Qiang, J., McCabe, P. J., Nuccio, V. F., and Persits, F., 2012, Shahejie-Shahejie/Guantao/Wumishan and Carboniferous/Permian Coal-Paleozoic total petroleum systems in the Bohaiwan basin, China: US Geological Survey Scientific Investigations Report 2011–5010.
Wu, R. S., 1986, Fractal dimensions of fault surfaces and the inhomogeneity spectrum of the lithosphere revealed from seismic wave scattering: Proceedings of the International Symposium on Multiple Scattering of Waves in Random Media and Random Rough Surface, 929–940.
Wu, R.-S., Xu, Z., and Li, X.-P., 1994, Heterogeneity spectrum and scale-anisotropy in the upper crust revealed by the German Continental Deep-Drilling (KTB) Holes: Geophysical Research Letters, 21, 911–914
| Heterogeneity spectrum and scale-anisotropy in the upper crust revealed by the German Continental Deep-Drilling (KTB) Holes:Crossref | GoogleScholarGoogle Scholar |
Wu, H.-Z., Fu, L.-Y., and Ge, H.-K., 2010, Quantitative analysis of basin-scale heterogeneities using sonic-log data in the Yanchang Basin: Journal of Geophysics and Engineering, 7, 41–50
| Quantitative analysis of basin-scale heterogeneities using sonic-log data in the Yanchang Basin:Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXhsFCrsb7N&md5=cf2bfaf73f5a018670411241684eb9c3CAS |