Abstract
Sequential indicator simulation is a commonly used method for discrete variable simulation in 3D geological modeling and a widely used stochastic simulation method, which can be used not only for continuous variable simulation but also for discrete variable simulation. In this paper, the X Oilfield in the western South China Sea is taken as an example to compare the sequential indicator simulation method and the Indicator Kriging interpolation method. The results of the final comparison show that the results of the lithofacies model established by the Indicator Kriging deterministic interpolation method are overly smooth, and its coincidence rate with the geological statistical results is not high, thus cannot well reflect the heterogeneity of the underground reservoir, while the simulation results of the lithofacies model established by the sequential indicator stochastic simulation method can fit well with the statistical law of the well, which has eliminated the smoothing effect of Kriging interpolation, thus can better reflect the heterogeneity of the underground reservoir. Therefore, the sequential indicator simulation is more suitable for the characterization of sand bodies and the study of reservoir heterogeneity.
Highlights
The X Oilfield in the western South China Sea is taken as an example to compare the sequential indicator simulation method and the Indicator Kriging interpolation method
The results of the final comparison show that the results of the lithofacies model established by the Indicator Kriging deterministic interpolation method are overly smooth, and its coincidence rate with the geological statistical results is not high, cannot well reflect the heterogeneity of the underground reservoir, while the simulation results of the lithofacies model established by the sequential indicator stochastic simulation method can fit well with the statistical law of the well, which has eliminated the smoothing effect of Kriging interpolation, can better reflect the heterogeneity of the underground reservoir
The values of the cumulative density function between [ZK, ZK+1] can be obtained by linear interpolation or other methods [13] [14]. Based on this concept, the sequential indicator simulation is proposed, for which one of the essential question is how to be faithful to the spatial connectivity pattern of known data and information, so that the model can reflect the heterogeneity of parameters
Summary
The Zhuhai Formation of X Oilfield in Zhujiangkou Basin belongs to fan delta front sedimentary environment, where estuarine dam, front sheet sand and dis-. Without being constrained by the assumption of normal distribution, this method, instead, converts the conditional data into indication data through a series of thresholds based on the existing data and uses Indicator Kriging to estimate the local conditional probability distribution at each network point according to the indicator variation function of each discrete variable. The author applies this method to study the lithologic characteristics of reservoir in the Zhuhai Formation in the X Oilfield in the Zhujiangkou Basin and compare it with the Indicator Kriging method through detailed analysis
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
