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Geological Modeling of Semideep Reservoir Based on Seismic Frequency Division Processing and Sedimentary Numerical Simulation

Authors: Zuobin Lv; Hongliang Song; Pengfei Wang; Na Fang; Bin Zheng;

Geological Modeling of Semideep Reservoir Based on Seismic Frequency Division Processing and Sedimentary Numerical Simulation

Abstract

Abstract The resolution of seismic data in the semideep reservoirs ranging from 1500m to 3000m is low, and reservoir prediction is difficult when well data are scarce (Xu et al. 2005; Liu et al. 2018; Pang et al. 2012; Wang et al. 2017). The sedimentary facies of the semideep reservoirs are mostly complex deltas, fan deltas, braided river deltas, etc. In addition, in the exploration evaluation stage and early development stage, the well pattern of offshore oilfields is sparse and well spacing is large. Especially in the early stage of oilfield development, well data are very few, so it is difficult to establish an accurate reservoir geological model. In order to solve this problem, this paper proposes a well-seismic integrated reservoir prediction technique based on seismic data frequency division processing and lithofacies distribution prediction technique based on sedimentary numerical simulation. On the basis of reservoir prediction, 3D reservoir geological modeling is carried out. With the reservoir prediction results as the constraint conditions, the sedimentary microfacies modeling is firstly developed, and then reservoir petrophysical modeling is carried out under microfacies constraints. The fine geological modeling of complex semideep reservoir is realized. Compared with the traditional geological model based on the constraint of 2D sedimentary microfacies map, the new modeling method has higher accuracy. The geological model established by the new method can more accurately predict the spatial distribution, porosity and permeability properties of reservoirs.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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