Seismic Facies Classification and Rock Typing to Better Understand Heavy Oil Reservoirs: A Case Study from North Kuwait

Moubarak, Hesham (KOC) | Al-Rashid, Tasneem (KOC) | Ren, Zubiao (KOC)

OnePetro 

Abstract

This paper describes seismic attributes approaches and rock typing in channelized reservoirs of North Kuwait. Seismic facies with a range of frequencies from 10 - 50 Hz, along with four other attributes: semblance, RMS frequency, instantaneous phase, relative acoustic impedance and RMS amplitude of shallow upper Cretaceous channelized system are calculated and the channel infill and overbank deposits are represented in maps. Five classes are used and found to be sufficient in the unsupervised classification method. The seismic facies classification was matched against the above-mentioned four attributes and found to correspond to them. The major channel components are illustrated with the figure 1. Additionally, the seismic facies classification workflow is summarized in figure 4. Results of seismic facies classification using Neuronal classification and log-based rock typing are illustrated in figures 11, 12, 13 & 21. The lessons learned from the use of different seismic attributes and rock typing in such heavy oil reservoirs are discussed.

Steam injections in shallow heavy oil targets come with a risk of breaching the thin cap shale sealing layer and not fully understanding the thickness and continuity of shale barriers within the reservoirs. This paper presents an investigation to mitigate those risks through different seismic attributes and rock typing for shallow Tertiary and Cretaceous reservoirs in North Kuwait which extended to a deeper heavy oil targets in neighboring fields. This work that studies all the key risk elements in such heavy oil reservoirs mitigates the drilling and steam injection risks of heavy oil field development. Those who utilize seismic data to map heterogeneities must realize that the changes we observe in our seismic events can be due to one of the following items: depositional environments, sweet spots, stratigraphic features, lithology, petrophysical properties such as porosity or fluid or clay content, geohazards, etc.

From a previous study presented this year at Geo 2018 for Tertiary targets, we concluded that Simultaneous geostatistical inversion (SGI) added much value in terms of delineating the shale barriers and enhancing resolution, in addition to estimating effective porosity for well releases.