Deep-water turbidity channels are rich in oil and gas

and a hot area of hydrocarbon exploration and development.The deep-water turbidity channels in Angola are taken for reservoir modeling based on multi-point geostatistics.Alluvsim algorithm based on sedimentary process was improved to capture deep-water channels' sedimentation and migration characteristics.First

the integral migration and deposition processes of turbidity channels were simulated by adding integral migration algorithm to Alluvsim algorithm.Second

the curvature index constraint was also added to represent the original curvature characteristics of turbidity channels

to simulate the morphology of fewer crevasses and higher sinuosity for the channels of Angola deep waters.In addition

we obtained the morphology and statistical characteristic parameters of turbidity channels in the study area through literature surveys on the geological knowledge database of deep-water turbidity channels in Angola.The so acquired training images of turbidity channels in the study area improved Alluvsim algorithm.Thereafter

a three-dimensional geological model of the deep-water channels in Angola was established based on Snesim algorithm of multi-point geostatistics

to reproduce the spatial distribution of these channels

in which the training image was the model

logging data were the conditions

and seismic data were the trend constraint.The inspection of the model result shows that the variogram calculated by the geological model is in good agreement with that obtained by seismic attributes

and the geological model set up in this study may be used for subsequent reservoir engineering and numerical simulation research to guide oilfield exploration and development.Apart from providing a complete modeling workflow for the application of multi-point geostatistics to actual reservoir modeling

the study also demonstrates the technical feasibility for the automatic generation of turbidity channel training images.