Abstract
Multi-point statistic method (MPS) can overcome the inherent disadvantages of traditional method based on variogram and object modeling, simultaneously allow the modeling progress, and become more flexible and rational. The algorithms based on variogram and gridding geological model are able to control the final result under the collection of samples’ data (well data) and another corresponding data (seismic). Though, these methods have trouble in modeling the shape of geological features. Then, object-modeling method can generate digitized geological features with responsible shapes; conversely, a final result in accordance with an input data is difficult to achieve. Combining the advantages of two mentioned methods, MPS describes the relationship of data in space based on the group of adjacent points or has a certain relationship, it allows the generation of digitized geological features corresponding with responsible shapes, and moreover, it is able to control the final result under a collection of input data (whose nature is still the pixel-based). The Oligocene reservoir, X field, was formed in fluvial/lacustrine and sedimentary mainly deposited in Northwest–Southeast, which is primarily affected by latitude—sub-latitude faults’ system. An Oligocene facies model of X field is built based on MPS, and it will show the geological features more clearly than the existing one. It also shows the remarkable ability on controlling the final result. MPS allows to combine a lot of different data (geology, seismic, outcrop, etc.) with the geological viewpoints which are shown by training image and itself proves the superiority over traditional methods. Duration of each model simulation is approximately 3000 s and huge size (over 15 million cells), and it is better while compared with 1717.8750 s in case of sequential simulation by SISIM method and default properties.
Highlights
Multi-point statistics method allows to combine different sources of information, plus the geological perspective shown by training image, and has proved its superiority compared to other traditional methods
Multi-point statistics method is a breakthrough in the field of geostatistics in particular and facies modeling in general
This method uses a training image to describe the relationship of data in space, overcoming the limitations of traditional facies modeling methods, which allow a more flexible and reasonable way in facies modeling
Summary
Based on assessing the shortcomings of X-field’s current facies model, multi-point statistics method was used to generate X-field facies model because of the following reasons: model (which has not been fully utilized in current facies model) (Wu 2007). Basically, multi-point statistics method is well known as a pixel-based method allowing a better control of the resulting model with well data (Wu 2007). The trend widen the flow in the river–lake transition zone to observe modern sediments, typically the Lago Poopó-Peru area (Fig. 6), reinforces this view Because they are seismic attributes based on grid cells, they cannot be used directly in facies model. These results provide the size and direction of the channel distribution within the study area. The sediment characteristics in these two areas are distinct, so it is necessary to develop two training images for each area This area has meandering flows and developed facies such as channel fill, crevasse splay, sheet flood, and overbank, and sometimes, there is mouth bar. To reach the required size, the ratio in the I-direction is 1.4 (Fig. 22)
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