Modeling Method

In view of the hassle that a single modeling technique can not expect the distribution of microfacies, a new concept of coupling modeling technique to comprehensively predict the distribution of sedimentary microfacies was proposed, breaking the culture that special sedimentary microfacies used the identical modeling method inside the beyond. because distinct sedimentary microfacies have extraordinary distribution characteristics and geometric shapes, it is greater correct to select exclusive simulation methods for prediction. in this paper, the coupling modeling technique turned into to set up the distribution of sedimentary microfacies with easy geometry thru the point indicating procedure simulation, and then predict the microfacies with complex spatial distribution through the sequential indicator simulation method. Taking the DC block of Bohai basin for instance, a high-precision reservoir sedimentary microfacies model become hooked up by means of the above coupling modeling method, and the version verification consequences showed that the sedimentary microfacies model had a high consistency with the underground. The coupling microfacies modeling approach had higher accuracy and reliability than the traditional modeling approach, which provided a brand new concept for the prediction of sedimentary microfacies.
The established order of a reservoir geological version in oil and gas strength resource exploitation is the important thing to reservoir description, and is also the core content and front of cutting-edge oil and gasoline reservoir geology studies [1] . Reservoir geological modeling refers back to the form, scale, path and superposition dating of the formation units of various tiers of reservoirs. for the reason that development of the concept and method of geological modeling, reservoir modeling technology has grow to be a famous research path. At gift, scholars have installed rich qualitative and quantitative models of reservoirs through outcrops, modern-day sedimentation, and flume experiments. these fashions have guided the satisfactory configuration anatomy of reservoirs in lots of vintage oil fields with dense properly styles, and have performed a massive function in the complete adjustment in the later level of oilfield development and in tapping the ability of remaining oil [2] . In latest years, with the slow quantitative improvement of geological research, a way to quantitatively signify the consequences of pleasant reservoir evaluation in the three-dimensional geological version has grow to be a studies hotspot, and has fashioned some realistic technical techniques, which has played a very good role in promoting the application of the consequences of geological model studies within the real oilfield improvement. The stochastic modeling approach of oil and gas reservoir is a brand new oil and fuel prediction generation Modeling Method advanced in current years. it is based on the acknowledged facts, takes the stochastic characteristic as the theory, and makes use of the stochastic simulation approach to generate an non-obligatory, equal opportunity reservoir model method. This approach has been hastily advanced [3] [4] . traditional three-D modeling generally only reaches the microfacies stage, while random modeling refers to the 3D quantitative simulation of the inner configuration interface and configuration unit of a unmarried microfacies sand body. Its essence is to refine the interface stage of the version, and convey the inner secondary interface of the reservoir into the quantitative characterization category of heterogeneity [5] [6] . handiest by way of accurately characterizing it within the model and enhancing the prediction accuracy of the remaining oil distribution can it better guide the later adjustment and tapping of the ability of the oilfield. At present, maximum modeling engineers commonly choose simplest one superior random modeling technique for reservoir sedimentary microfacies prediction [7] [8] . however, due to the fact the distribution traits and geometric morphology of various sedimentary microfacies have unique laws, it’s miles tough to simulate the distribution of microfacies with exceptional morphological traits through a random reservoir modeling approach, so the accuracy of the geological version hooked up isn’t always excessive. for this reason, the author proposed a coupling stochastic geological modeling approach to comprehensively expect the distribution regulation of reservoir sedimentary microfacies, that is, to combine the goal based totally point indicating manner modeling method with the pixel-based totally sequential indicator simulation technique to establish a reservoir microfacies geological model, which furnished a new idea for predicting sedimentary microfacies.