Research On Intelligent Inversion Of Tight Clastic Rock Reservoir Parameters And Quantitative Characterization Of Fractures

The Shihezi Formation,Shanxi Formation and Taiyuan Formation in the Hangjinqi Exploration Area,northern Ordos,are tight clastic reservoirs with complex lithology,variable frameworks,and well-developed fractures.Different from conventional reservoirs,how to effectively identify the physical properties of tight reservoirs? Organic matter,gas content?How to identify cracks and quantitative calculation of crack parameters? Become a key scientific and technological issue currently facing.Because the previous methods for studying conventional reservoirs did not have much reference value,their effects are not obvious for tight clastic reservoirs,and fractures are developed in this area.Fractures are not only an important storage space,but also an important factor in increasing oil and gas production.Therefore,in order to obtain reliable tight oil and gas resources,new methods and exploration methods must be adopted.Therefore,it is necessary to use multi-model,multi-parameter,multi-dimensional,and unconventional methods to study and explore the different parameters of tight clastic reservoirs.Aiming at the key problems faced by tight reservoirs,especially the problem of parameter inversion,this paper studies the methods and models that are suitable for obtaining tight clastic reservoir parameters(mineral composition,physical properties,organic matter,gas-bearing properties,etc.)in the target area.Fracture identification and development quantitative characterization methods,combined with the target block well times,verify the validity and advancement of the method model,and realize a comprehensive evaluation characterization model for tight clastic reservoirs.First,for the complex lithology of the mineral composition,based on the volume structure of the mineral composition of the reservoir,use the calibrated core data to construct an overdetermined equation and use machine learning to calculate and analyze the corresponding composition of different logging responses.The volume value provides a favorable pavement for the analysis of physical properties and the porosity of fractures;secondly,with the recognition of the lithology of the reservoir as the starting point,a set of plates and lithology spectrums for identifying different lithologies are established;in the direction of lithology Calculate various parameters(porosity,permeability,TOC,gas saturation,etc.)of complex reservoirs in tight clastic rock under the effect of natural properties to form a set of inversion methods suitable for complex reservoir parameters in the target area;then,use different types of fractures Based on the well logging response,through a variety of algorithms of machine learning,the logging response characteristics corresponding to different fractures are learned,a model for accurate fracture identification is established,and a method for characterizing the degree of fracture development is further formed.Aiming at the tight clastic complex reservoirs in the northern Hubei area,a comprehensive evaluation model of the reservoir was constructed by fusing lithology data,physical property data,gas-bearing data,and fracture development data,and established a comprehensive evaluation classification standard to achieve Quantitatively and intuitively predict the spectra of different grades of reservoirs,and compare the gas test results,which are intuitive and effective,and effectively support the efficient exploration of the target interval in the northern Hubei area.Therefore,this article proposes a series of method models to promote the quantitative characterization of lithology,organic matter,oil(gas)and other reservoir parameters of the tight clastic complex reservoirs and the identification and characterization of fractures,and can provide effective The fractured reservoirs provide services for the exploration and development of tight reservoirs at home and abroad.