AVO Technique Applied In Gas-bearing Detection In Jingbian Gas Field

The He8gas reservoir of Jingbian gas field, which is a typical tight sandstone gas reservoir, is with the characteristics of low porosity, low permeability, low abundance, deep burial and thin reservoir thickness. As the sandstone reservoir of delta plain and front facies, the H8reservoir of study area is thin and has strong heterogeneity, the lithology change rapidly in space, what is more, as the weak relative changes in geophysical characteristics to low porosity and hydrocarbon saturation, effective reservoir prediction and hydrocarbon detection become a difficult point. This paper, based on predecessors’work and the objective reservoir characteristics, carried out the seismic rock physics analysis of He8reservoir, analyses hydrocarbon-bearing reservoir’s geophysical response characteristics, optimizes the effective elastic sensitive parameters; using AVO forward modeling to identify the AVO response characteristics and abnormal types; then using the AVO attribute analysis and pre-stack elastic parameters inversion techniques to interpret the reservoir and gas-bearing layer.This study achieved good results in reservoir prediction and hydrocarbon detection of the He8tight gas reservoir of Jingbian gas field. The research achievements are like the followings:1、The thickness of He8reservoir in the study area is about50meters, the lithology is thin sands and mudstones interbed. On the whole, the P-wave velocity and impedance of sands are higher than mudstones, but when the sands are filled with gas, the P-wave velocity will be decayed and overlapped with mudstones; Gamma ray can distinguish sands from mudstones, but just like P wave, it cannot detect the fluid properties. So the conventional logging data is hardly to detect fluids in study area.2、The S wave velocity has been estimated through rock Petrophysics methods. As the research shows, the curve shapes of S-wave velocity and P-wave velocity are unanimous in non-reservoir layers, but in reservoir layers, especially the gas-bearing layers, P-wave velocity and density become smaller while S-wave velocity have no significant changes, and the Poisson ration have the low values. It gives the foundation of Petrophysics to use pre-stack data with P-wave and S-wave information to distinguish lithology and detect hydrocarbon in study area.3、Based on P-wave velocity, S-wave velocity and density, many elastic parameters can be available, such as P and S wave velocity ration(γ), impedance (Zp, Zs), Poisson ration(σ) and other parameters(bulk modulus:K, young modulus:E, shear modulus:u, Lame parameter:γ). Through comprehensive analysis, three parameters which are sensitive to fluids can be picked to detect hydrocarbon in study area, they are Lame parameter, bulk modulus or bulk modulus/shear modulus ration, Poisson ration.4、Based on the deep analysis on He8hydrocarbon-bearing reservoir’s geophysical response characteristics, the thesis launched forward modeling studies of He8hydrocarbon-bearing reservoir by using logging data of drilled wells. It can be found that, the gas-bearing sands in study area are belonged to the second and fourth type:the second type sands are the good reservoirs, in which the porosity is larger than10%, the permeability is larger than1md; the fourth type sands are the moderate reservoirs with medium physical properties.5、Using AVO attributes(such as intercept, gradient and pseudo Poisson ration) analysis and pre-stack inversion results(P and S wave impedance, P and S wave velocity ration and Lame parameter) to quantitative interpret and analysis the gas-bearing reservoir in study area, the interpret results coincide with the drilling data. So using AVO attributes analysis and elastic parameter inversion techniques are effective in hydrocarbon detection in study area.6、The sedimentary facies of H8formation in study area includes the delta plain and front facies, and the favorable reservoir are mainly located at distributary channels. Through the analysis of RMS amplitude and mean impedance of post-stack seismic data, it can find the law of the sand distribution. Then combined with physical properties of reservoir in study area to evaluate the He8reservoirs comprehensively, two favorable areas can be picked out. After using the AVO attributes and LMR inversion analysis to detect hydrocarbon, these two favorable are the effective gas-bearing areas.This thesis applied seismic rock physics analysis and AVO techniques in Jingbian gas field, and formed an effective method for reservoir prediction and hydrocarbon detection in Jingbian tight sandstone gas-bearing reservoirs, which have important practical significance.