Fluid sensitivity study of elastic parameters in lowmedium porosity and permeability reservoir rocks

In this article,based on the acoustic measurements of core samples obtained from the low to medium porosity and permeability reservoirs in the WXS Depression,the densities and P and S wave velocities of these core samples were obtained.Then based on these data,a series of elastic parameters were computed.From the basic theory and previous pore fluid research results,we derived a new fluid identification factor（F）.Using the relative variations,Ag/w and Ao/w,of the elastic parameters between gas and water saturated samples and between oil and water saturated samples,λρ,σHSFIF,Kρ,λρ-2μρ,and F as quantitative indicators,we evaluate the sensitivity of the different fluid identification factors to identify reservoir fluids and validate the effects by crossplots.These confirm that the new fluid identification factor（F） is more sensitive for distinguishing oil and water than the traditional method and is more favorable for fliud identification in low to medium porosity and permeability reservoirs.

Well-Based Quantitative Reservoir Characterization of Eocene Sokor-1 Formation, Termit Basin, Niger

The Eocene Sokor1 Formation is proven oil reservoir rocks in the Termit sub-basin. These sandstone intervals are deeply buried, highly heterogeneous in character and characterized by Low Contrast Low Resistivity (LCLR) log responses. Petrophysical and quantitative well-based rock physics interpretations were integrated for property estimations, fluid and lithology typing in reservoir characterization. Six (6) reservoir sandstone intervals were identified, delineated and correlated across five (5) wells. The estimated petrophysical properties showed that the Eocene Sokor1 sandstones have averagely good reservoir properties with sand_5 interval exhibiting exceptional reservoir properties. Vp/Vs vs. AI and μρ vs. λρ elastic cross-plots color coded with reservoir properties (Vsh and Φ), show distinct and well separated data clusters signifying hydrocarbon bearing sandstones, brine sandstones and shales/mudstones in the 3D crossplot planes with varying seismic elastic property values in each well thereby, enhancing reservoir characterization and providing information’s about the burial history, reservoir quality and property distribution in the sub-basin. The analysis suggests that, although the reservoir interval has averagely good petrophysical properties in all wells, the seismic elastic crossplots show that these properties are much better distributed in wells 2 and 3 than in wells 4, 5 and 9. Therefore, sand_5 reservoir interval in wells 2 and 3 is likely to be more hydrocarbon bearing and productive than wells 4, 5 and 9 in the sub-basin.

Application of Multi-Attribute Crossplots to Tight Gas in X Area, Western China

The gas-bearing reservoir in X area is mainly the tight sandstone reservoir characterized by low porosity and permeability, frequently lateral variation and poor connectivity of single sand. The previous research results reveal that the general seismic attributes analysis cannot meet the requirement of fluid identification. This is because the relationship between seismic attributes and their implication is uncertain and ambiguous, which decreases the precision of both reservoir prediction and fluid identification. To overcome the problem, multi-attribute crossplot technology is proposed from the mathematical statistical point of view rather than the correspondence between the seismic attributes and their geological implication. In this method, the wells which have the same statistical law are classified firstly, and then all the interest wells are retained while the wells beyond the statistical law are eliminated, and the seismic attributes sensitive to the same types of eliminated wells are optimized and used to generate crossplots. The nonzero area of their crossplots results just predicts the potential distribution. The discontinuity of subsurface geological conditions results in the non-continuous shape and the seismic bin lead to the mosaic form. The optimization of sensitive attributes relative to the same types of wells is independent from each other, and thus the order of attributes in crossplots does not affect the final prediction results. This method is based on the statistical theory and suitable for the areas such as the study area abundant of lots of well data. Application to X area proves the effectiveness of this method and predicts plane distribution about different types of gas production. Due to the effect of faults and other geological factors, the partition prediction results using multi-attribute crossplots reach 95% of coincidence which is obviously and far higher than the results of the whole area. The final prediction results show that the potential areas with medium and high gas production are mainly concentrated in the northern part of the study area, where lots of development research will be strengthened.

Application of AVO attributes for gas channels identification, West offshore Nile Delta, Egypt

The offshore part of the Nile Delta is considered one of the most prolific provinces for gas production andfor future petroleum exploration. Amplitude Variation with Offset (AVO) analysis supported by composite logs considered as one of the best-advanced techniques enables the interpreter to understand theseismic data. It is used to generate a new view of the output results, especially for the identification of gaszones as gas channels by using pre-stack AVO attributes that based on the intercept product gradient(A*B) and the Scaled Poisson’s Ratio Change. Free gas, regardless of the percentage show obvious AVOanomaly. Well log data, including gamma-ray, resistivity, and Vp sonic logs are used in the seismic data towell tie and in the generation of the synthetic seismogram. Seismic data conditioning processes withcheck-shot correction is performed to improve the resolution of the reflection events and signal to noiseratio. AVO attributes technique, as a direct hydrocarbon indicator, including AVO gradient analysis andAVO crossplot separate the gas levels in the sand-shale sequences. The identified gas-bearing zonesconsistent with well log data responses. As the main conclusion, we show the visual evidence for the gasbearing zones by interpreting different AVO responses due to the changes in fluid and rock types.