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川西北双鱼石地区栖霞组地震资料优化处理及裂缝预测技术应用
引用本文:于 豪,黄家强,兰雪梅,刘军迎.川西北双鱼石地区栖霞组地震资料优化处理及裂缝预测技术应用[J].科学技术与工程,2020,20(22):8933-8942.
作者姓名:于 豪  黄家强  兰雪梅  刘军迎
作者单位:中国石油勘探开发研究院,北京100083;中国石油西南油气田分公司勘探开发研究院,成都610041
基金项目:国家科技重大专项“下古生界-前寒武系地球物理勘探关键技术研究”
摘    要:川西北双鱼石地区栖霞组气藏勘探开发潜力大,是目前四川盆地加快天然气增储上产的重要领域。目前该地区已经进入开发阶段,面对勘探阶段的地震资料品质及裂缝预测结果尚不能满足开发的需求,需要在已有资料的基础上进一步优化处理,提高资料精度。将该区用于构造解释的叠后地震资料进行了解释性处理,通过扩散滤波和反射系数反演技术,去除了噪声并提高了分辨率,改善了地震资料的品质;通过多属性RGB(red-green-blue)融合技术定性预测了裂缝发育特征,利用BP(back propagation)神经网络和DFN(discrete fracture network)离散建模技术量化预测了裂缝的密度、长度和发育方向。预测结果表明,双鱼石地区栖霞组裂缝总体为北东-南西向伴随断裂走向呈条带状展布,局部发育有北西-南东向的裂缝。北部山前带由于构造活动影响,裂缝发育密度高,南部裂缝发育密度稍低。地震预测结果与成像测井资料吻合,验证了方法的有效性。

关 键 词:扩散滤波  反射系数反演  RGB融合  BP神经网络  DFN离散建模
收稿时间:2019/9/27 0:00:00
修稿时间:2020/5/6 0:00:00

Application of Seismic Data Optimal Processing and Fracture Prediction in the Shuangyushi Block, Northwest Sichuan
YU Hao,HUANG Jia-qiang,LAN Xue-mei,LIU Jun-ying.Application of Seismic Data Optimal Processing and Fracture Prediction in the Shuangyushi Block, Northwest Sichuan[J].Science Technology and Engineering,2020,20(22):8933-8942.
Authors:YU Hao  HUANG Jia-qiang  LAN Xue-mei  LIU Jun-ying
Institution:PetroChina Research Institute of Petroleum Exploration and Development
Abstract:There is a great potentiality for exploration and development of Qixia Formation in the Shuangyushi Block, Northwest Sichuan. It is an important area for accelerating the increase of natural gas reserves and production. At present, the region has entered the stage of development. The seismic data quality and fracture prediction results at exploration stage are still unable to meet the needs of development stage, which needs to further optimize processing based on existing data to improve the data accuracy. In this paper, Interpretative processing technologies such as diffusion filtering and reflection coefficient inversion are used to improve the seismic data quality of structural interpretation, which can remove the noise and improve the resolution. The fracture characteristics are qualitatively predicted by multi-attribute RGB fusion technology. And the density, length and direction of cracks are well quantitatively predicted by BP neural networks and Discrete fracture network. The results show that the cracks are generally developed in the northeast-southwest direction along with the fault in the Shuangyushi Block, while partial area is northwest-southeast. Due to the influence of tectonic activities, the northern piedmont belt has a high density of crack development. The density of crack development in the south is slightly lower. The results of seismic prediction are in good agreement with the imaging log data, which proves the effectiveness of the method.
Keywords:Diffusion  filtering    Reflectivity  inversion    RGB  fusion    BP  neural networks  Discrete fracture  network
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