BP神经网络模型在元素-矿物转换中的应用

doi:10.3969/j.issn.1672-9803.2023.03.001

摘要/Abstract

摘要： XRF元素录井与XRD全岩矿物分析录井在岩性识别、潜山界面卡取、储层精确评价等油气勘探过程中发挥着越来越重要的作用。XRD全岩矿物分析录井可直接获得矿物含量,但是样品制作相对复杂、周期较长,故在实际勘探钻井中XRF元素录井应用更为广泛,但是仅依靠XRF元素录井得不到单矿物的含量,不能精准得到目的层矿物的类型。利用测井中的氧闭合模型思路,将XRF元素录井得到的元素转化为氧化物,依据氧闭合模型对XRF元素录井数据进行校正。据此利用渤海某区块的XRF元素录井和XRD全岩矿物分析录井数据,根据XRF元素录井测量的元素含量计算氧化物含量,依据氧闭合模型对元素氧化物含量进行校正,并将校正后的元素数据作为输入,XRD全岩矿物分析录井测量的矿物含量作为输出,用BP神经网络模型多次训练,建立了该地区元素和矿物之间的转换关系,用于对实际数据进行分析,元素恢复矿物符合率达到80%以上。

关键词: BP神经网络, 元素录井, 氧闭合模型, 元素矿物转换, 全岩录井

Abstract: XRF element logging （XRF for short） and XRD whole rock minerl analysis logging（XRD for short） play increasingly important roles in oil and gas exploration process such as lithology identification buried hill interface capture, accurate reservoir evaluation and so on. XRD can directly obtain mineral content, but sample preparation is relatively complex and the cycle is long, so XRF is widely used in actual exploration drilling. However, only relying on XRF can not get the content of single mineral, and can not accurately get the mineral type of target layer. Using the idea of oxygen closure model in well logging, the elements obtained from XRF are transformed into oxides, and the XRF data can be corrected according to oxygen closure model. In this paper, the data of XRF and XRD in a block of Bohai Sea are used： calculating the oxide content according to the element content measured by XRF, correcting the element oxide content according to the oxygen closure model, taking the corrected element data as input and the mineral content measured by XRD as output. The conversion relationship between elements and minerals in this area is established by training with BP neural network model for many times, which is used to analyze the actual data. The coincidence rate of elements recovering minerals is over 80%.

Key words: BP neural network, XRF, oxygen closure model, element-mineral conversion, XRD

中图分类号:

TE132.1

张文颖, 袁胜斌, 陈伟, 韩学彪, 刘永华. BP神经网络模型在元素-矿物转换中的应用[J]. 录井工程, 2023, 34(3): 1-6.

ZHANG Wenying, YUAN Shengbin, CHEN Wei, HAN Xuebiao, LIU Yonghua. Application of BP neural network model in element-mineral conversion[J]. Mud Logging Engineering, 2023, 34(3): 1-6.

参考文献

[1] 占蓉,邹筱春,李芳.随钻X线衍射分析录井技术应用研究[J].录井工程,2012,23(4):1-5.
ZHAN Rong, ZOU Xiaochun, LI Fang.Application and research of the logging technology for X-ray diffraction analysis while drilling[J].Mud Logging Engineering,2012,23(4):1-5.
[2] 方锡贤. X射线衍射全岩矿物分析录井技术应用拓展[J].录井工程,2016,27(1):14-18.
FANG Xixian.Mud logging technology of X-ray diffraction whole rock mineral analysis[J]. Mud Logging Engineering,2016,27(1):14-18.
[3] 赵利娟. X射线荧光元素录井技术标准应用方法研究[J].中国石油和化工标准与质量,2017,37(10):146-147.
ZHAO Lijuan.Study on application method of X-ray fluorescence element logging technical standard[J].China Petroleum and Chemical Standard and Quality,2017,37(10):146-147.
[4] 余意,倪朋勃,王建立,等.元素录井技术在渤中A区块潜山界面卡取中的应用[J].录井工程,2021,32(1):33-38.
YU Yi, NI Pengbo, WANG Jianli, et al.Application of element logging in the determination of buried hill interfaces in Bozhong A block[J]. Mud Logging Engineering,2021,32(1):33-38.
[5] 胡云,谭忠健,张建斌,等.岩屑成分分析在渤中19-6潜山界面识别中的应用[J].中国海上油气,2020,32(6):70-76.
HU Yun, TAN Zhongjian, ZHANG Jianbin, et al.Application of cuttings composition analysis in identification on BZ 19-6 burial hill surface[J]. China Offshore Oil and Gas,2020,32(6):70-76.
[6] 陈伟,倪朋勃.元素录井技术在岩性识别及地层界面卡取中的应用[J].中国石油和化工标准与质量,2022,42(6):190-191.
CHEN Wei, NI Pengbo.Application of element logging technology in lithology identification and formation interface determination[J].China Petroleum and Chemical Standard and Quality,2022,42(6):190-191.
[7] 郭睿. 元素俘获能谱测井矿物计算方法研究[D].西安:西安石油大学,2017.
GUO Rui.Study on mineral calculation method of element capture energy spectrum logging[D]. Xi'an:Xi'an Shiyou University,2017.
[8] 匡立春,王振林,孙仲春,等.氧闭合模型的构建方法及氧闭合模型的应用方法:201410850434.0[P].2016-07-27.
KUANG Lichun, WANG Zhenlin, SUN Zhongchun, et al. Construction method of oxygen closure model and application method of oxygen closure model: 201410850434.0[P].2016-07-27.
[9] 于静,王伟,王振林,等.一种基于多元回归分析的元素测井氧闭合模型[J].粘接,2020,2(42):44-48.
YU Jing, WANG Wei, WANG Zhenlin, et al.An oxygen closure model of element logging based on multiple regression analysis[J]. Adhesion,2020,2(42):44-48.
[10] 王娜娜. 神经网络在测井岩性识别中的应用[D].北京:北京化工大学,2009.
WANG Nana.Application of neural network in logging lithology identification[D]. Beijing: Beijing University of Chemical Technology,2009.
[11] 杨辉. 致密砂岩天然气储层的测井识别与评价及BP与SA混合算法在测井中的应用[D].长春:吉林大学,1998.
YANG Hui.Logging identification and evaluation of tight sandstone natural gas reservoir and application of BP and SA hybrid algorithm in logging[D]. Changchun:Jilin University,1998.
[12] 刘天时,赵越,马刚.基于BP神经网络的油气钻井成本预测[J].西安石油大学学报(自然科学版),2010,25(1):87-90.
LIU Tianshi, ZHAO Yue, MA Gang.Prediction of oil and gas drilling cost based on BP neural network[J]. Journal of Xi'an Shiyou University(Natural Science Edition),2010,25(1):87-90.
[13] 李舟波,王祝文.科学钻探中的元素测井技术[J].地学前缘,1998,5(1-2):119-130.
LI Zhoubo, WANG Zhuwen.Technique of elemental logging in science drilling project[J]. Earth Science Frontiers,1998,5(1-2):119-130.
[14] 孙建孟,姜东,尹璐.地层元素测井确定矿物含量的新方法[J].天然气工业,2014,34(2):42-47.
SUN Jianmeng, JIANG Dong, YIN Lu.A method for determining mineral content by formation element logging[J]. Natural Gas Industry,2014,34(2):42-47.

相关文章 15

[1]	杨毅, 熊亭, 毛敏, 袁胜斌, 曹英权. 惠州凹陷X构造潜山复杂岩性识别与流体评价方法[J]. 录井工程, 2023, 34(3): 89-96.
[2]	马海, 范光第. 基于BP神经网络模型的随钻测井曲线预测[J]. 录井工程, 2023, 34(2): 22-27.
[3]	何成山. 元素录井技术在大港油田奥陶系潜山界面卡取中的应用[J]. 录井工程, 2023, 34(2): 28-33.
[4]	向克满, 唐诚, 王崇敬, 梁波, 凡刚. 川南D区水平井靶区小层的UMAP算法判别图板研究[J]. 录井工程, 2023, 34(1): 18-23.
[5]	温海涛, 郭明宇, 阚留杰, 苑仁国, 王建立. 元素特征组合法在BZ凝析气田开发井潜山界面预警中的应用[J]. 录井工程, 2023, 34(1): 29-34.
[6]	胡宗敏, 张立刚, 罗光东, 王曲, 邓圣甲, 冯伟. 基于元素录井的深层火成岩抗钻特性评价[J]. 录井工程, 2023, 34(1): 24-28.
[7]	韩学彪, 袁胜斌, 陈伟, 张文颖. 氧闭合模型在元素录井中的探索应用[J]. 录井工程, 2022, 33(4): 13-18.
[8]	李柯, 唐诚, 王崇敬, 梁波, 施强, 欧传根. 川南页岩小微尺度断层井震结合识别方法研究[J]. 录井工程, 2022, 33(4): 125-132.
[9]	刘有武, 杨春龙, 曾志勇, 孟繁涛, 张培鑫. XRF元素录井技术在鄂尔多斯盆地西缘乌拉力克组页岩储层识别评价中的应用[J]. 录井工程, 2022, 33(3): 27-33.
[10]	刘达贵, 杨琳, 牟兴羽, 莫倩雯, 安虹伊, 唐锐峰. 页岩气铂金箱体录井响应特征及其在川南水平井随钻解释中的应用[J]. 录井工程, 2022, 33(3): 78-83.
[11]	彭业雄, 黄治梁, 李仕芳, 贾浩, 方铁园, 刘芳芳. 多种录井技术在水平井射孔井段优选中的综合应用[J]. 录井工程, 2022, 33(1): 60-64.
[12]	唐诚, 王崇敬, 梁波, 顾炎午, 李柯. 基于机器学习算法的页岩气评价参数计算模型研究[J]. 录井工程, 2021, 32(4): 18-22.
[13]	夏良冰, 赵彦泽, 胡云, 王建立, 苑仁国, 阚留杰. 基于敏感元素特征谱图的岩性识别方法[J]. 录井工程, 2021, 32(4): 47-52.
[14]	沈柏坪, 李志水, 王丹丹, 马铭杰, 孟祥文, 史晓波. 基于元素录井的拟合伽马在地层卡取中的应用[J]. 录井工程, 2021, 32(4): 33-36.
[15]	丁冬, 王建立, 陈卓, 刘少峰, 李亚男. 泥岩掉块层位还原技术研究与应用[J]. 录井工程, 2021, 32(4): 28-32.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed