Research On Interpretation Methods Of Reservoir Parameters In Lamadian Oil Ifeld

Lamadian Oilfield is located in the northern of Daqing Changyuan，the structural controlof layered sandstone gas cap oil field, Since2000has entered the development phase of thehigh water cut, injection so far developed more than30years. Long-term waterflooding,reservoir parameter, pore structure, fluid distribution Dengjun produce a series of changes,these changes will be reflected in the logging curves. Inspection wells, core analysis, indoorphysical model tests and field monitoring data show that the thick oil-based heterogeneousmulti-reservoir sandstone oil field water cut is increased to90%later, there is a seriousineffective and inefficient circulation, and are distributed in a thick oil and oil sheet.As Lamadian oilfield reservoir of the gas cap, gas sands development，the reservoirparameters to explain the research is no longer adapted to the reservoir properties of the highwater cut stage to explain the results of error is large, the technology is relatively backward,high water cut of comprehensive adjustment, the perforation programming and other oil fielddevelopment work has had a negative impact. For the current stage of development for nowlogging a series of parameters to explain the promotion system, according to oil field tofurther improve the reservoir of electrical and physical properties of the standard,re-interpretation method to carry out reservoir parameters, in order to solve the flooding layerof interpretation accuracy, low work efficiency technical issues, and thus the use of varioustypes of reservoir of Lamadian oilfield conditions and flooding extent there is an objectiveand correct understanding to guide the effective development of the high water cut of oilfields to meet the factory needs.Explain the method by for Lamadian of reservoir parameters in-depth study to find forLamadian oilfield logging curve values, that is, form values, the thickness-weighted value andthe average area of the average value of three methods. Secondly, depending on the floodedlaw, through the computer log curve modeled as a feature vector, then the use of neuralnetworks for the first time to identify the flooded layer, according to the characteristics ofLamadian Oilfield, the second to identify the flooded layer. The final development of theparameters to the interpretation chart prepared in accordance with the status of the LamadianOilfield flooded layer interpretation software...