Study Of Well-logging Comprehensive Evaluation In The Gasi E₃² Area

In order to resolve the problem about complex reservoir lithology, great variation in physical property, seriously heterogeneous, available reservoir delineation, identification of fluid type in Gasi E₃² area it is necessary to study the well-logging comprehensive evaluation of complex reservoir. The lithology of the Gasi reservoir is difficult to identify. Most lithology is muddy limestone or algal limestone. It is very difficult to decide the formation lithology just using core observation, oil production testing data, physical property data and conventional logging data. In the thesis we firstly develop a technique. The technology is combined with FMI and ECS from Schlumberger, and calibrated by core. It is based on observing core and the law of fracture development after thorough analysis and calibration. Algal limestone is the important reservoir lithology in this zone. The logging response and thickness statistics of algal limestone are analyzed by logging cross plot. The wells with considerable thickness and typical FMI image characteristics are selected to do lateral comparison. The lateral comparison can also be carried out by core calibration and rock thin section.We analyze the main storage space of reservoir, the fracture feature (attitude, types), forming and filling mechanism. The fracture parameters are quantitatively calculated by FMI. According to the calibration of fracture porosity, that full diameter cores analysis permeability is greater than 0.1 and that conventional core analysis permeability is smaller than 0.1 are used to decide whether the cores has the fracture. The statistical analysis is performed on those cores. A good geological result was obtained. The rock electric characteristics (a, b, m and n) are determined. The reservoir effective porosity, oil saturation, permeability and formation water resistivity are also obtained. The pie chart, bar chart, cross plot and logging synthetic graph are applied to study the relationship of the four properties'relations.According to the difficulty of identifying fluid in this area, we apply some methods to identify the fluid type and develop the index of fluid identification. Those methods include induction-lateral ratio method, NMR shift differential spectrum method, S-wave transit time overlap, P-wave and S-wave velocity ratio method, difference-ratio method of P-wave equivalent elastic modulus, ratio method of fluid acoustic impedance, difference-ratio method of elastic modulus ratio, hydrogen index overlap method, fluid compressibility method. A good result was obtained by those methods.The 3D geological model of the Gasi area is generated using random model based on PETREL software. According to the geological property of the research area, we apply sequence indicator simulation method if the reservoir type is discrete variable. Sequence Gauss simulation method is used if the type of reservoir property is continuous variable. Structural model (single well model, fault model and bedding model) and property model are built. The 3D distributions of reservoir parameters are established based on structural model. Three advantage oil distribution of the oil field are pointed out through overlap of the reservoir parameters distributions.