The Analysis Of AVO Abnormal Response Characteristics Of The Reservoir In Gangbei Region

The study area is located in the northern region of the Binhai fault which includes the two main blocks, and covers about70km2. This area has been developed more than thirty years, and changed the development mode for many times. The main target strata are Bin Ⅰ oil sand group in the lower Shahejie first section and BinⅢ,BinⅣ oil sand group in the Shahejie second section, having the lithology of dark mudstone interbedded with light grey sandstone. The faults and terrain in this area are very complex. Generally, the terrain to the north of Binhai Fault shows a trend of higher in southwest and lower in northeast. And the distribution of sand presents thicker in the eastern part and thinner in the western partBecause the sand in Gangbei region distribution is very complicated, so it is difficult to predict the characteristics of its plane distribution. Now we need to adopt effective methods to predict reservoir sand and the distribution of oil and gas which will provide feasible basis before drilling. Some of the difficulties in the summary of the research in Gangbei area are the difficulties to figure out fluid distribution characteristics, and also to predict the reservoir because of the small difference in P-wave impedance between the reservoir and surrounding rock. In order to solve the above problem, we try to introduce the AVO analysis technology into this area, which can help to identify the physical characteristics of rock and its AVO anomaly response, to determine a good lithology and fluid prediction. This can provide strong technical support for reservoir development and well location in the late high water development stage in complex fault block area. The main content of this study include rock physics analysis, AVO forward modeling, AVO inversion and plane distribution prediction of oil and gas.Rock physics research based on geological background and logging data which is the basis of AVO analysis can be concluded in the following four parts:1. The necessary processing and correction of logging curves;2. The prediction of density and shear wave;3.The analysis of logging curve characteristics of the oil layer, water layer, dry layer and overlying mudstone;4. The analysis of the relationship between the parameters (such as P-wave velocity, S-wave velocity, poisson’s ratio, density and impedance parameters) and lithology as well as fluids. Rock physics analysis contributes to figuring out differences between reservoir and non-reservior section, and also the sensitive attributes parameters that can distinguish lithology and fluids.AVO forward modeling is based on complete Zoeppritz equation and can accurately simulate the variation trend of amplitude with the change of incident angle. According to the study on the AVO response of actual gas, oil and water layer, we can establish AVO detection marker for the typical oil and gas formation in the study area. Through the fluid replacement, we can simulate the AVO response characteristics in six conditions which include the100%water,25%oil,50%oil,75%oil,100%oil and100%gas, and then summarize the change rule.Based on Shuey approximate equation in the theory of inversion research, three basical AVO attributes (intercept P, slope G and curvature C) often can be extracted from the seismic data. And through combining them can obtain more attributes that can quantify the relative value of rock elastic parameters such as P-wave velocity, S-wave velocity, density, poisson’s ratio and so on. By analyzing attribute anomalies related to oil and gas, and referring to conclusions of rock physics and the forward research, the right combination of attributes can be determined to predict lithology and fluid. And then we can finish the plane distribution prediction of oil and ga, also can delienate the favorable area, and simultaneously combine the logging interpretation results with production data.to analyse the reliability on the result.After going through the four aspects of research contents mentioned above,1have summarized the AVO abnormal responses characteristics of the reservoir in Gangbei area and have solved the problem of fluid distribution in the study area, and can make the following conclusions:1. In Rock physics the velocity of oil layer, water layer, dry layer are higher than the overlying mudstone, the difference in velocity can be used to distinguish sandstone and mudstone; Density of dry layer is higher than mudstone and the oil layer and water layer are lower than that of mudstone, so relative density attribute can be used to separate the dry layer from the oil-water layer; Reservoir has the characteristics of lower poisson’s ratio, so the use of poisson’s ratio attribute can distinguish reservoir to a certain extent.2. In AVO forward modeling study of actual wells:the AVO anomaly response of oil bearing layers in the study area belong to the Ⅱ1class, and the characteristics are that when P value is small and positive and G value is negative, polarity reversal may occur; the AVO anomaly response of gas bearing layers belongs to the Ⅱ2class, the characteristics are that P value is small negative and G value is negative; The AVO anomaly response for the water bearing layers is that, the P value is positive, and the G value is positive. From the research of forward modeling with fluid change, conclusions are that:If the fluid situation in reservoir changes from100%water to100%oil, along with the increase of oil saturation, P value decreases, and G value decreases to negative and belong to the Ⅱ1class AVO abnormal responses; If it changes to100%of gas, the P value continues reducing to negative and belong to the Ⅱ2class AVO abnormal responses. So we can consider using attributes related to the slope G to distinguish oil and water layer.3. The cross plot analysis of inversion P/G attributes can test if the inversion result based on the actual seismic data and the forward modeling based on logging data at wells are consistent, these shows reliability of prediction result at well point and other areas. Through the analysis of single-well AVO abnormal attribute, we can compare and optimize the AVO attributes. Finally, both P-wave velocity and S-wave velocity difference attributes are selected to differentiate lithology by looking for positive anomaly area. On the basis of the lithologic prediction, the relative density, slope and poisson’s ratio attributes are combined to predicting oil and gas. The contrast at well points shows that predicting results is reliable.4. The results of plane distribution prediction of oil and gas show that:For BinⅠ oil sand group, the favorite area is the northern part of the study area; For BinⅢ oil sand group, the favorite area is the north-eastern and western part of study area; For Bin Ⅳ oil sand group, the favorite area is the central part of study area.