Logging identification method of depositional facies in Sinian Dengying Formation of the Sichuan Basin

The sedimentary facies/microfacies,which can be correlated with well logs,determine reservoir quality and hydrocarbon productivity in carbonate rocks.The identification and evaluation of sedimentary facies/microfacies using well logs are very important in order to effectively guide the exploration and development of oil and gas.Previous carbonate facies/microfacies identification methods based on conventional well log data often exist multiple solutions.This paper presents a new method of facies/microfacies identification based on core-conventional logs-electrical image log-geological model,and the method is applied in the fourth member of the Dengying Formation(Deng 4)in the Gaoshiti-Moxi area of the Sichuan Basin.Firstly,core data are used to calibrate different types of facies/microfacies,with the aim to systematically clarify the conventional and electrical image log responses for each type of facies/microfacies.Secondly,through the pair wise correlation analysis of conventional logs,GR,RT and CNL,are selected as sensitive curves to establish the microfacies discrimination criteria separately.Thirdly,five well logging response models and identification charts of facies/microfacies are established based on electrical image log.The sedimentary microfacies of 60 exploratory wells was analyzed individually through this method,and the microfacies maps of 4 layers of the Deng 4 Member were compiled,and the plane distribution of microfacies in the Gaoshiti-Moxi area of the Sichuan Basin was depicted.The comparative analysis of oil testing or production results of wells reveals three most favorable types of microfacies and they include algal psammitic shoal,algal agglutinate mound,and algal stromatolite mound,which provide a reliable technical support to the exploration,development and well deployment in the study area.

Adaptive multi-resolution graph-based clustering algorithm for electrofacies analysis

Logging facies analysis is a significant aspect of reservoir description.In particular,as a commonly used method for logging facies identification,Multi-Resolution Graph-based Clustering(MRGC)can perform depth analysis on multidimensional logging curves to predict logging facies.However,this method is very time-consuming and highly dependent on the initial parameters in the propagation process,which limits the practical application effect of the method.In this paper,an Adaptive Multi-Resolution Graph-based Clustering(AMRGC)is proposed,which is capable of both improving the efficiency of calculation process and achieving a stable propagation result.More specifically,the proposed method,1)presents a light kernel representative index(LKRI)algorithm which is proved to need less calculation resource than those kernel selection methods in the literature by exclusively considering those"free attractor"points;2)builds a Multi-Layer Perceptron(MLP)network with back propagation algorithm(BP)so as to avoid the uncertain results brought by uncertain parameter initializations which often happened by only using the K nearest neighbors(KNN)method.Compared with those clustering methods often used in image-based sedimentary phase analysis,such as Self Organizing Map(SOM),Dynamic Clustering(DYN)and Ascendant Hierarchical Clustering(AHC),etc.,the AMRGC performs much better without the prior knowledge of data structure.Eventually,the experimental results illustrate that the proposed method also outperformed the original MRGC method on the task of clustering and propagation prediction,with a higher efficiency and stability.

Integrative method in lithofacies characteristics and 3D velocity volume of the Permian igneous rocks in H area, Tarim Basin

This paper introduces horizon control, seismic control, logging control and facies control methods through the application of the least squares fitting of logging curves, seismic inversion and facies-controlled techniques. Based on the microgeology and thin section analyses, the lithology, lithofacies and periods of the Permian igneous rocks are described in detail. The seismic inversion and facies-controlled techniques were used to find the distribution characteristics of the igneous rocks and the 3D velocity volume. The least squares fitting of the logging curves overcome the problem that the work area is short of density logging data. Through analysis of thin sections, the lithofacies can be classified into eruption airfall subfacies, eruption pyroclastic flow subfacies and eruption facies.

Study on sedimentation distribution based on cooperative analysis of geologic-geophysical in less well area: A case study of Suweiyi sandstone in the DB area, Kuqa Depression in Tarim Basin

The Kuqa Depression in Tarim Basin develops fan deltaic,braided river deltaic,and lacustrine sedi-mentation,espeially extensive braided river deltaic sedimentation,in the Cretaceous-Paleogene Sys-tems.However,fine sedimentary pattern of the Kuqa Depression and North Tarim Uplift belt since the Middle Cenozoic still needs to be studied.As a combination zone of the Kuqa Depression and North Tarim Uplift,the sedimentary characteristics of the DB area in the southern margin of the east of the Kuqa depression have been paid more attention.To better understand the sedimentary framework in the Kuqa Depression and North Tarim Uplift in the Mesozoic and Cenozoic,through joint geologic-geophysical study,sedime ntation of sandstone at the bottom of the Paleogene Suweiyi Formation in the DB area and its peripheral area is investigated.Sedimentary facies and sandstone distribution in the area are identified through core observation,component analysis,logging interpretation and seismic inversion.Based on seismic facies analysis,sedimentary facies distribution in the area is delineated.Results show that sandstone at the bottom of the Paleogene Suweiyi Fommation in the DB area and its peripheral area is developed in shore shallow lacustrine beach-bar facies.The beach-bar arenaceous sediments are mainly distnibuted in the southern DB area and the shallow lacustrine mudstone is developed in northern DB area,showing obvious north south di ferentiation charactenistics.