With the popularization and application of fast drilling technology in Sichuan-Chongqing gas provinces,the returned cuttings are fine and even powdered,so the traditional cutting lithology identification methods are n...With the popularization and application of fast drilling technology in Sichuan-Chongqing gas provinces,the returned cuttings are fine and even powdered,so the traditional cutting lithology identification methods are not applicable any longer.In this paper,qualitative lithology identification and quantitative interpretation based on element logging were conducted on the key oil and gas bearing layers in this area according to the principle of elemental geochemistry.The study results show that:(1)different lithologies can be identified easily because of their different element logging characteristics.For example,basalts have the element characteristics of 0.35<Fe/Si<0.55 and Ca/(Na+K)<4.00,while sedimentary rocks have Fe/Si<0.35 or>0.55.(2)Clastic rocks,carbonate rocks,sulphate and transition rocks in the category of sedimentary rocks can be identified based on the element combination of(Al+Si+Fe)and(Ca+Mg+S).Among them,clastic rocks have(Al+Si+Fe)>31%,carbonate rocks have(Al+Si+Fe)<8%and(Ca+Mg+S)<36%,and sulphate rocks have(Al+Si+Fe)<5%and(Ca+Mg+S)>36%.(3)Then,based on the element combination of(Si+K+Ca)tSi/Al and(Al+Si+Fe+K)t(Ca+S)/Mg,sandstone,mudstone(shale),gypsum,dolomite,limestone and transition rocks can be identified.Finally,a qualitative identification chart and a set of quantitative interpretation software of element logging on key horizons in Sichuan-Chongqing gas provinces were developed to make this method convenient for field application.This method was applied on site in ten wells(such as Well MX207)in Sichuan-Chongqing gas provinces.It is indicated that the coincidence rate of lithology identification is in the range of 88.75-95.22%(averaging 92.42%).Obviously,it can satisfy the requirements of fast lithology identification while drilling of key oil and gas horizons in Sichuan-Chongqing gas provinces.展开更多
In the process of shale gas drilling,geo-steering plays an important role in shale gas drilling.This paper analyzes the constituent elements of shale formation,and selects the most suitable constituent elements of sha...In the process of shale gas drilling,geo-steering plays an important role in shale gas drilling.This paper analyzes the constituent elements of shale formation,and selects the most suitable constituent elements of shale formation.A particle swarm optimization algorithm based on improved inertia weight and acceleration factor is proposed to optimize the parameters of support vector machine.The lithology identification model of shale formation is established based on IPSO-SVM.According to the experimental analysis based on the field historical data,the recognition rate of IPSO-SVM is increased by 17.79%,10.17%and 8.05%,respectively,compared with SVM,GA-PSO and PSO-SVM.In terms of running time,the running time of IPSO-SVM is 13.76s and 9.5s shorter than that of GA-PSO,PSO-SVM,respectively.By comparing the experimental results of different models,IPSO-SVM has the advantages of strong robustness,strong reliability,high accuracy and fast convergence speed.It provides a theoretical basis for precise geo-steering and finding the optimal shale layer.展开更多
基金Project supported by the Science and Technology Project of CNPC Chuanqing Drilling Engineering Co.,Ltd“Element logging features of key horizons and application in SichuaneChongqing gas provinces”(No.:CQ2014B-14-1-1).
文摘With the popularization and application of fast drilling technology in Sichuan-Chongqing gas provinces,the returned cuttings are fine and even powdered,so the traditional cutting lithology identification methods are not applicable any longer.In this paper,qualitative lithology identification and quantitative interpretation based on element logging were conducted on the key oil and gas bearing layers in this area according to the principle of elemental geochemistry.The study results show that:(1)different lithologies can be identified easily because of their different element logging characteristics.For example,basalts have the element characteristics of 0.35<Fe/Si<0.55 and Ca/(Na+K)<4.00,while sedimentary rocks have Fe/Si<0.35 or>0.55.(2)Clastic rocks,carbonate rocks,sulphate and transition rocks in the category of sedimentary rocks can be identified based on the element combination of(Al+Si+Fe)and(Ca+Mg+S).Among them,clastic rocks have(Al+Si+Fe)>31%,carbonate rocks have(Al+Si+Fe)<8%and(Ca+Mg+S)<36%,and sulphate rocks have(Al+Si+Fe)<5%and(Ca+Mg+S)>36%.(3)Then,based on the element combination of(Si+K+Ca)tSi/Al and(Al+Si+Fe+K)t(Ca+S)/Mg,sandstone,mudstone(shale),gypsum,dolomite,limestone and transition rocks can be identified.Finally,a qualitative identification chart and a set of quantitative interpretation software of element logging on key horizons in Sichuan-Chongqing gas provinces were developed to make this method convenient for field application.This method was applied on site in ten wells(such as Well MX207)in Sichuan-Chongqing gas provinces.It is indicated that the coincidence rate of lithology identification is in the range of 88.75-95.22%(averaging 92.42%).Obviously,it can satisfy the requirements of fast lithology identification while drilling of key oil and gas horizons in Sichuan-Chongqing gas provinces.
文摘In the process of shale gas drilling,geo-steering plays an important role in shale gas drilling.This paper analyzes the constituent elements of shale formation,and selects the most suitable constituent elements of shale formation.A particle swarm optimization algorithm based on improved inertia weight and acceleration factor is proposed to optimize the parameters of support vector machine.The lithology identification model of shale formation is established based on IPSO-SVM.According to the experimental analysis based on the field historical data,the recognition rate of IPSO-SVM is increased by 17.79%,10.17%and 8.05%,respectively,compared with SVM,GA-PSO and PSO-SVM.In terms of running time,the running time of IPSO-SVM is 13.76s and 9.5s shorter than that of GA-PSO,PSO-SVM,respectively.By comparing the experimental results of different models,IPSO-SVM has the advantages of strong robustness,strong reliability,high accuracy and fast convergence speed.It provides a theoretical basis for precise geo-steering and finding the optimal shale layer.
