已知井 meaning in Chinese
fixed well
Examples
- Moreover , the thesis applied this method to interpret volcanic rock , sandstone rock and carbonate rock individually . at last , the thesis tested the interpretation results by comparing the interpretation results and the well data which is already confirmed right by the real geological circumstances
并应用该方法分别对火山岩剖面、砂泥岩剖面和碳酸盐岩剖面的若干口已知井进行了解释，将解释结果与已知井进行对比、分析和评价，检验方法应用效果。 - First , basing on carefully post - processing and correcting seismic data , inverse the wave impendance and physical parameters of reservoir , making the researches of seismic attributes are made , then , the relationship between seismic attributes and oil - gas parameter are used to make regression analysis and calculating physical character parameter of reservoirs and oil - gas . basing on avo attributes analysis of known well , the correlation of avo attributes and oil - gas can be applicated in whole area
首先对地震资料进行精细叠后处理及统一校正，在此基础上进行波阻抗反演、物性参数反演、地震属性的研究，并利用油气参数与地震属性之间的关系进行回归分析，计算油气及储层的物性参数；从已知井处的avo属性处理及分析入手，研究avo与油气的关系并应用于整个研究区；计算出剖面的吸收系数并研究其与储层分布和油气之间的关系。 - Reservoir productivity was studied by using seismic data , based on the extraction of seismic wave attribute , a neural network train set was established based on known well productivity and well - site seismic wave attribute by using the neural network , the distribution of oil and gas productivity in lg area was predicted
就利用地震资料研究储层产能开展了探索性研究，以地震波属性提取为基础，以神经网络为手段，根据已知井的产能与井旁地震波属性建立神经网络训练集，对lg区块油气产能分布进行预测。 - Secondly , based on the improved algorithmic of computing the multi - fractals spectrum of seismic records , aiming at the given seismic data , we extract some character parameters of multi - fractals . following that , we select the useful parameters . finally , we fulfill the successful forecast of single geodesic and the whole area of upside layer of aotaoxi in some oil field based on oil attributes of the wells we have known , using the method of grey pattern identification , and get good comments from some experts of the same vocation
论文首先介绍了一般分形和多重分形的基本理论和算法：其次，用作者提出的一种求地震记录多重分形谱的改进算法，对给定的地震道数据进行多重分形特征参数的提取；接着优选出油气识别用的多重分形特征参数；最后，根据已知井位的油气属性，用灰色模式识别方法实现了某油fr奥陶系上部储层单测线及区域油气产出前景的成功预测，得到了同行专家的好评。