首页> 外国专利> METHOD FOR DETERMINING PLACES mortgaged production wells while RAZBRABOTKE HYDROCARBONS FIELD

METHOD FOR DETERMINING PLACES mortgaged production wells while RAZBRABOTKE HYDROCARBONS FIELD

机译:确定RAZBRABOTKE油气田中抵押生产井位置的方法

摘要

A method of determining places emplacement wells in the development of hydrocarbon fields comprising drilling exploratory wells within the field followed by coring and holding therein geophysical and seismo studies, the construction of maps reservoir properties of the formation, which is isolated zones most probable development of reservoirs, at designated areas laying the production wells, characterized in that the isolated complex geological genetic regionally with a common p sprostranennym oil and gas bearing horizon with belonging to it investigated portion and the reference deposit on the test portion is conducted exploratory drilling followed by coring and sludge and holding therein geophysical studies, the results of which determine the effective H layer thickness and the effective pore volume by the formula: where H - the effective thickness of the reservoir, measured at the points of its intersection portion of the test wells, K. average value for the formation porosity reference field, objectified elyayut for the reference field threshold value of the effective pore volume V, wherein the collector of the breed of lithology neftegazonosen; of seismic data for the reference field is determined set of dynamic, kinematic, structural attributes of the seismic wavefield, which are used in forming the training sample for the trained neural network based on the values ​​of the effective pore volume Vdlya wells; using a trained neural network is isolated by attribute significance
机译:一种确定油气田开发中的安置井的方法,包括在该油田内钻探性井,然后进行取心并进行地球物理和地震研究,构造地层的储层特性图,这是最有可能开发储层的孤立区域,在指定的铺设生产​​井的区域进行,其特征在于,进行了勘探活动的钻探,然后进行取心和污泥并保存在地球物理研究中,其结果通过以下公式确定有效H层厚度和有效孔隙体积:其中H-储层的有效厚度,在测试井的相交部分测得,K 。地层孔隙度平均值场,针对有效孔隙体积V的参考场阈值的客观elyayut,其中岩性neftegazonosen的收集器;参考场的地震数据的确定是确定地震波场的动态,运动学,结构属性的集合,用于基于有效孔体积Vdlya井的值形成训练神经网络的训练样本;通过训练的神经网络通过属性重要性来隔离

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号