| As the exploration and development of Daqing oil field entering into the middle-late stage, the conditions for producing steadily and the development situation have changed a lot. It is confronted with many difficulties, such as production decline, increase in costs, oil field development being more difficult. In order to achieve the goal of40million tons, Hailaer oil field has been the focus, which is located in northeastern inner Mongolia autonomous region. Three oil blocks in the Mongolian Toson-Uul basin were successfully acquired by Daqing Oil Field.A set of clastic reservoirs and pyroclastic rock reservoirs developed in Tanan sag of the area being studied. Complex formation lithology, complex pore structure and strong heterogeneity of pyroclastic rock reservoirs make the logging response characteristics changing in a wide range, which influence the accuracy of logging interpretation. In addition, study in pyroclastic rock is still at relative low level by far and rare sound theory could be guideline. With the exploration and development continually being further, pyroclastic rock reservoirs are gaining more and more attention. Exploration indicates that pyroclastic rock reservoirs exist in many parts of the world, with great reserves and a great prospect of development. So, it was very important to research lithological identification and calculation methods of reservoir physical properties for the development of pyroclastic rock reservoirs.Logging response characteristics of different lithology are analyzed in this paper. Mainly based on conventional log data, combining with coring analysis, well testing, mercury intrusion data and etc., the relationship among lithology, physical properties, oil property and electrical property of reservoir are reached. Based on the Logging response characteristic of different lithology and "four-property relationship" of reservoir, reaches on lithology identification and parameter of logging interpretation were made.Lithology identification is one of the most important tasks in logging interpretation. It provides lithology data for geology study and evidence for logging interpretation to correct choose interpretation method and parameters. Only conventional logging data can be found in this area, how to improve the coincidence rate of lithology identification is a difficult question in reservoir study. In this paper, cross-plot method and neutral network are the main methods for lithological identification. On the basis of logging response characteristics of different lithology and "four-property relationship" of reservoirs, DEN, AC, GR and LLD are optimized to make cross-plot. Then based on cross-plot, the sample points of neutral network were selected as input neuron to identify lithology model. Then interpretation model was established based on different lithology. Compared with geo-logging, coring analysis, the result of lithology is accurate and reliable. This approach makes the same lithology having similar logging response and lithology characteristic. Then we translate anisotropic, nonlinear issues into homogeneous, linear issues.The calculation of reservoir parameters, as an important section in logging interpretation with the aim to know the characteristic of property, provides the reliable reservoir property information for real production. According to the result of lithology identification, the reservior of pyroclastic rock in this area including shale content, porosity, permeability and saturation was calculated based on different layer and lithology.The porosity model in the study area was established used "Core calibration Logging"and PCA(Principal Component Analysis), and permeability was established using regression and distinguish lithology in this paper. Types of reservoir were sorted out with capillary pressure data which were analysised pore-structure. On this base, the water saturation was calculated by Archie formula in this area; Compared with oil testing, the plate of oil and water was made. The program has been applied to process wells of the object area, the accordance of log interpretation rose to85%. |
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