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摘要:采用瞬变电磁勘探方法探测新疆煤炭火烧区含水性,在瞬变电磁法勘探常规电阻率计算的基础上,利用大定源回线优化反演技术,结合测井、钻探及地质资料形成三维数据体,并利用自主开发的三维可视化软件进行资料解释,经钻探验证效果良好。
关键词:瞬变电磁;优化反演;火烧区
新疆地区煤炭资源丰富,但煤层火烧区分布亦广泛,对煤层破坏及开采影响巨大,煤层火烧后往往形成较大的裂隙,使得煤层顶底板地层导水性加强,在大气降水以及周边河流的补给下,容易形成较大的水区,直接威胁井下安全,因此,针对火烧区特别是富水区的探测显得尤为重要,本文主要探讨采用瞬变电磁(TEM)反演技术对火烧区含水性精细化探测的应用效果。
1 研究区地质、地球物理特征
本次课题组选择新疆准南煤田某矿作为研究区,该区内主要分布侏罗系下统八道湾组(J1b),为该区主要含煤地层,由下而上沉积环境呈现出不同的相变模式,底部主要为湖泊—沼泽相沉积,向上逐渐伴有河流相的含煤粗粒碎屑岩建造,岩性主要以灰—灰黑色泥岩、泥质粉砂岩、细砂岩、砾岩和煤层组成,夹少量厚层状中、粗砂岩,地层总厚为699—1379.42米。含大于0.30米的煤层35层,编号煤层为2l层,煤层平均总厚79.21来,按地层平均厚1045.61米计。含煤系数为7.6%。该组地层与下伏三叠系上统郝家沟组(T3h)呈平行不整合接触,与上覆三工河组(J1s)为整合接触。
根据以往物探及测井资料可知,该区地层电阻率在10~ 102.5Ω·m,其中以地表较为干燥的第四系覆盖层电阻率最高,达102.5Ω·m,以含水火烧区最最低约10Ω·m。而黑色泥岩以及泥质粉砂岩亦为低阻反应,以往电磁法勘探手段难以区分,往往根据电阻率绕曲及低阻圈闭并结合解释人员经验进行划分含水区边界,人为因素大,因此需要在资料解释阶段引入约束反演,提高资料解释的精细度。
2 工作方法及技术
瞬变电磁法(Transient electromagnetic method,TEM)属时间域电磁测深法,又称“纯异常场法”,它是利用阶跃波形电磁脉冲激发,利用不接地回线向地下发射一次场,在一次场的间歇期间(断电后),测量由地下介质产生的感应二次场随时间的变化来达到寻找各种地质目标体的一种引人注目的地球物理勘探方法。该方法对低阻反映灵敏、分层明显,是自八十年代在国内煤矿采空区探测、防治水等方面广泛应用并在近几年取得长足发展的煤矿物探新技术。
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
瞬变电磁法的工作原理是:在地表敷设不接地线框或接地电极,输入阶跃电流,当回线中电流突然断开时,在下半空间就要激励起感应涡流以维持断开电流前已存在的磁场,并且此涡流场随时间以等效涡流环的形式向下传播、向外扩展,利用不接地线圈、接地电极或地面中心探头观测此二次涡流磁场或电场的变化情况,用以研究浅层至中深层的地电结构。由于是在没有一次场背景的情形下观测纯二次场异常,因而异常更直接、探测效果更明显、原始数据的保真度更高。(其工作原理见右图)。
为了后期反演工作及三维解释的需要,本次试验采集按照40×40m的规则网度采集,采用大定源回线参数,共完成了5777点的原始资料采集。
资料处理方法
对经过验收的原始资料进行滤波、排序等基础处理,为进一步的计算和处理工作做好准备。
瞬变电磁法观测数据是各测点各个延时(时窗)的瞬变感应电压,同一个测点不同延时(时窗)的感应电压不仅与某个深度的地层电阻率具有一定的相关性,而且和该深度上覆地层电阻率相关。
二次场归一化感应电压由于信号小,易受各种人文电磁、地表因素干扰,因此去除非地层电性产生的感应电压是瞬变电磁处理的首要目标。采用了直接的畸变数据剔除和非线性滤波两种方法。
瞬变电磁场法对于地表条件的适应性是比较强的,资料处理主要是针对电磁干扰的。对一些干扰大的测点先做单点平滑,然后再通过剖面图视电阻率等值线的形态进行分辨。一般来说,孤立的、非常密集的封闭圈往往不是真正的地质异常,需将其再次平滑。
当然,平滑的基础是受电磁干扰的瞬变实测衰减曲线仍保持了形态上的完整。为此,当干扰很大时除加大供电电流外(180-200A),每个测点上的重复观测次数多达7-8次直到获得较为理想的曲线为止。
尽管感应电压高对应电阻率低,但不同时间的瞬变电磁二次场感应电压跨跃了5、6个数量级(甚至更大),而且不直观。将归一化瞬变感应电压换算成视电阻率、视纵向电导、视深度等直观参数是瞬变电磁数据处理不可缺少的,也是最基础的,它符合深度多少米电阻率多少的常规解释要求。几种主要参数计算公式如下
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
-------------------------晚期视电阻率 式中μ0=4π×107,M为发射磁矩M=I·L2,t为时窗时间,q为接收线圈的有效面积,VZ是感应电压
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
-----------------------纵向电导
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0aHBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/wAALCAAeAHUBAREA/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQAAAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/9oACAEBAAA/APf6KKKydT1O40/VNNixB9mu5fJYuWDBsEjBxt6gDB654qoviRo9O1e5nhRpLKZ0ijjP+tXaGQ+xIYVrQXRSOGK+lgS8aIyOiHAwMbiM84GRzUVnrFrfXZt4PMLeSJwxQhWRiQrA++Dj6VoVBcXIt5LdCjN50nlgj+H5S2T/AN8/rS21yt1EZUUiMnCMf4x6j2qaiqWlakmrWIu4opY42dlTzAAWAJG4YJ4OOKu1keILt4IrOCGV4pbm6RNyHlUX53J9tqkH61FH4iDaXZXrQIguo/MVXnVcDt165GDVi41FmudLgQFRebmZ1OcBV3YB9+PwzUv9rRf8+17/AOAsn+FU7uS0vWzLFqeMDaq28gCsDkMBt+8D3+lVZbPS5UwbfU1YvE7usEgMhjxt3cc9B9cVo3N7aXdvLBPZ3rxyo0bj7LIMqRgjOKz9JK6fdXs8sN05mZFjK2spKxIoChiV653Hj1rWXVInYL9nvRk4ybZx+uKz187VmuLKSNWFldMnnSDr8isMe5Em0kdg3rVrTvt1jpIGoKZ7hZH4g+bKljtwOOMY47VZF8Psxne2uUAbbsMRLH3wM8VE2qQujKbe+wRji1kH9Khs7u0sLKC0t7S+WGBBGgNrIcKBgdqv210l0GKxzJt/56xMmfpkc1I8UchBeNGIBALKDgHrSoixoqIoVVGAqjAApk9vHP5ZfIaNt6MOqnp/IkfjXOJrV/tvIVIkmbVms4WKgCNNgfn8iAT3IrV0rU0vLOF1jusND5nmTKAOpBUkcZyPy5qtYaxqNw11Jc6dAltChdTbXRmkfuBs2DqOevcVHJcXV14kurOC9mjX7BGwiCr+6Z2cb+RnIC9DxntWw0htIYEYT3BLLGXC5Of7zYwAPU1ji/uZfEKwi8xazOfs5jUMreWMSRt3DbgTnpjjqOduC3jt4ykY6sWYnqxPUmpajnmjtreWeVgscSF3Y9gBkmsyw12O7kCSxrbnyombfIOJJASI/cgYP41Pf3si213HARb3K4igluEIjaVh8mPUZIBpNEnmubAzTPKWLspSULujK/Kykrw3zKxz6EVo0UVVXTrJEmRbSFVnbfKAgw7ep9T71Y8tDH5exfLxt244x6YpscEMTu8cUaM+N7KoBbAwM+uBxTZoBJHME2xySptMgUE9DjPrjNR6bZLp2nQ2isGES4yFxnn0qSKztoZWlit4kkbqyoATzk/rU1FQXdrHe2zW8ufKcjeox8wzyp9j0Psap3eh2tx5XlIlvsdWYxxgbwBjB/Cr80EVwmyaJJEzna6gjPrSxRRwRrHEioi9FUYAr//Z)
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhDAAXAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAAAAAABAAEAgAAAAAECAwICRAEAOw==)
------------------视深度 上述视电阻率、视深度是处理应得到的基本参数,根据资料的实际情况应进行滤波、优化反演等处理。
建立如下目标函数ψ的模型,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
式中,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhOAANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAgA1AAkAhQAAAAAAAAMAAAADCAsLDQsGAw0KCAMGCw0LCwgDBAoLDQ0LCgQDCAoEAAgDAwgKDQgIDQ0IBAQAAAAAAwgDAAMDAAsLCwgECAQEBAMGCgQIDQAECgAABAoLCwoEAwgKCgsLCgMECgQABAAEBAQEAwMDCAECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwaoQIBwSCwKDYIBwVgsBJ6BAwCRUDAXjCVzO2wouUKE4wEwQMTkbUS5kEzSXARlUvmCsZbLMiJ1YgIZc2kFGg0bhmAAERwdFHZcEU9SAB5kSIcTHxIaQhGHT19yUHYFSl5LoqBalA9mQpVlAoUDIJtHIadDqQGkHAq5XAsiVl2cSLO1nIobSAEbibvKTM2TnX0BI24kvEuEid/gYWNcBiWr4ehMVMRFWEtBADs=)
,d是数据向量,m是模型向量,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhDQANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAwAJAAkAhAAAAAAAAAQAAA0LCgMGCw0KCAMDCAsLDQgIDQ0IBAoEAwgKDQQECgQIDQAECgsGBAoEAAQABAoLDQADCAECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwUnIAAMQmAGhAgUxrEiapKqqrIMDE2aDZ04gMeCBunRRhHJMWGauFQhADs=)
是正演模拟函数,e是残差向量。其中
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
的分量
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhDAANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAgAJAAkAhAAAAAAAAAQECgsGAwQIDQQAAAADCAsICgoLDQMGCwoEAAADBAQDAwgKDQQAAw0KCAMDCAsLDQAECg0LCwgDAw0IBA0LCgAECAgDAAECAwECAwECAwECAwECAwECAwECAwUrICCOgCWQ40CQVmEcCDokyloWC9OMltM8kEhqNZCMJpRGJWATKQIXjFEUAgA7)
为
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhFgANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAgAVAAkAhQAAAAAAAAsGAwAAAwgKDQ0IBAAECg0LCwgDAwsGCAoLDQ0KCAMDCAsLCwgECAsLDQsLCggGCwAABAoKCAMAAwgKCwgDAAMGCwQIDQgEAwMDAwgGBAoEAw0ICAQDCAoLCwsGBA0LCgQABAMECggDBAMAAAoEBAgKCgECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwZnQABAECgOCMKkshAwJA8IZEKhVC4YDcdDeIVEhpIJpWK5AJgSapIZwAAOGUZGszEDOEglvoNceD4WGCBIIR5bSSEiVAIYBRcLIwckVAVOSQslRQFpJgqMmGaMVaOjHCeGpKlCAkdVQQA7)
(归一化感应电动势,单位
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
);
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
为地电模型的电阻率向量,可令
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhEAANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAwANAAkAhQAAAAAAAAMAAAADCAsLDQAAAwgKDQMABAoLDQ0LCwgDAAsIBA0ICAMDAAMGCwgGCAgDAw0LCgQEBAQAAwgICwoEBAoKCAMDCAsGCAoEAAQIDQ0IBAsGAwAECggGCgMGCggIDQ0KCAAABAECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwECAwZHQAAgJBgQhENBwYAMHRDChMKIBCyeQkbDUU08IMyIZMJsUsCAiuVyRGIQGc1Gw+l0PQDOxyPVVEMgeUtOUEIbAQFycogihUEAOw==)
为模型单元个数,且每一
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhDAANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAIAAgAJAAkAhAAAAA0LCgQECgsGAwQIDQ0ICgoLDQoEAAAABAoKCAMAAwgKCwgDAAMGCw0LCwgEAwMDCAMDAwgGBA0KCAQDCAoLCwsGBAgKDQ0IBAMECggDBAoEBAMAAAECAwECAwECAwUvICCOQCCQ40CgYmGwwEEMSKIsTCM6D/REEh1gQqkwCJaLCNOYZByaF2BjUE04whAAOw==)
为取对数后的电阻率值(即
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhGAANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAgAWAAkAhAAAAAAAAAQABAoLDQsGAwAABA0LCwgDBAgDAA0LCgADCAsLDQQAAAAECg0KCAMAAAMGCwoEAA0IBAgDAwgKDQQDCAQIDQMDAwAAAw0ICggGCgECAwECAwECAwECAwECAwVaYCIMQGme6EkUZOqixjEYSKAsCRMEzek8AQggNiAIIxAJxDChmBKVheRGjFgAkgbNtjARrsqhjNBTSq4nIhEb3N5+ux7AcXlgnC9AhmTQlL55JxE7dwBQXSchADs=)
)。正则化参数λ是一个正数。正定矩阵V起残差向量e之协方差的作用,其是数据误差的一种度量。ψ的第二项是为了获得稳定的解而对地电模型的一种约束。本程序将矩阵L取为简单的二阶微分算子,即Lm近似为Δ(
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,R0lGODlhGQANAHcAMSH+GlNvZnR3YXJlOiBNaWNyb3NvZnQgT2ZmaWNlACH5BAEAAAAALAEAAgAXAAkAhAAAAAAAAAQABAoLDQsGAwAABA0LCwgDBAgDAA0LCgADCAsLDQQAAAAECg0KCAMAAAMGCwoEAA0IBAgDAwgKDQQDCAQIDQMDAwAAAw0ICggGCgECAwECAwECAwECAwECAwVaYCIMQGmeKEoUZOqmxjEYSKAsQMIEQXM6jwAEEBsQhpGhBGKYUEyJykJyK0YsAImPZsOVCNglUUbwiSXYU7GYFXJvACDPF788MM9XKUMyaL5peiYRPHg5UighADs=)
)。 非线性共轭梯度(NLCG)直接求解最小二乘的极小化问题,突破了
线性化迭代反演的框架。非线性共轭梯度的模型序列由一系列的一元极小化或沿着计算的搜索方向的线性搜索所确定,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
搜索方向是对线性共轭梯度的近似,其迭代格式为,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
式中,
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
。
成果解释
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
通过上述资料处理及优化反演,形成一个以40×40m为单元网格的三维数据体,并采用课题组自主开发的三维可视化解释软件,对该数据体按照解释资料形成剖面、水平切片以及联井剖面等,进行资料的最终解释,三维可视化效果如下图2,三维可视化效果图。资料解释过程中,采用该可视化软件可以根据需要叠加上已知的地质、钻孔、测井数据,形成地质、钻探、测井、瞬变电磁一体化的三维数据体,可对地下地质体完成初步的三维定位和显示,更好的提高解释精度及直观效果,极大的提高了解释效率。
![](https://www.soolun.com/img/pic.php?url=data:image/png;base64,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)
本课题的研究区域内煤层较厚,各层煤都有燃烧,煤层的顶、底板比较破碎,火区地面塌陷严重。所以空区基本都有冒落现象,视电阻率剖面上的相对高阻对应着老窑和燃烧后形成的空区或者是这些区域冒落后形成的松散破碎带。相对低阻对应着火烧区含水体、老窑积水区、煤层燃烧区。在对异常体进行解释的时候,要在充分利用已知的地形地质资料的前提下,除视电阻率值的高低外,在判断异常方面还要考虑视电阻率等值线的形态、地形、地表电性不均匀程度、观测点原始数据质量等因素。
当然,实际的解释过程还是遵循有已知到未知,有剖面到平面的过程。其中下图3即为对验证钻孔部分局部放大的剖面显示。从图上可见,在标高500至900m,图形左侧小出现大面积低电阻率区,物探推测为火烧区含水体,与后期钻探验证情况完全吻合。
5.结论及建议
通过本次优化反演形成的瞬变电磁数据在低背景电阻率区域探测水区效果较好,能够在低电阻率的砂泥岩区见到较为明显的含水区边界,并经后期钻探验证,准确率较高;采用三维切片的方式使得解释过程更为直观、高效;反演过程中较好的利用了地质模型和综合测井资料,使得反演成果更为接近真实地质情况,有效的解决了瞬变电磁深度误差较大的问题。
由于本研究区后期发现浅部有大量的老窑采空区存在,在瞬变电磁资料上反应不明显,可见基于大定源回线的反演技术针对浅部(深度小于100m)低阻体探测存在一定的缺陷,使用过程中应结合浅层具体情况采用其他的方法进行补充。
参考文献:
[1]李貅,瞬变电磁测深的理论与应用,陕西科学技术出版社,2002。
作者简介:
苗圃(1967—)高级工程师,中国地质大学工程硕士学位,1990年工作,先后从事新疆煤田灭火处技术科科长、副总工程师、新疆煤炭科学研究所所长等工作。
关键词:瞬变电磁;优化反演;火烧区
新疆地区煤炭资源丰富,但煤层火烧区分布亦广泛,对煤层破坏及开采影响巨大,煤层火烧后往往形成较大的裂隙,使得煤层顶底板地层导水性加强,在大气降水以及周边河流的补给下,容易形成较大的水区,直接威胁井下安全,因此,针对火烧区特别是富水区的探测显得尤为重要,本文主要探讨采用瞬变电磁(TEM)反演技术对火烧区含水性精细化探测的应用效果。
1 研究区地质、地球物理特征
本次课题组选择新疆准南煤田某矿作为研究区,该区内主要分布侏罗系下统八道湾组(J1b),为该区主要含煤地层,由下而上沉积环境呈现出不同的相变模式,底部主要为湖泊—沼泽相沉积,向上逐渐伴有河流相的含煤粗粒碎屑岩建造,岩性主要以灰—灰黑色泥岩、泥质粉砂岩、细砂岩、砾岩和煤层组成,夹少量厚层状中、粗砂岩,地层总厚为699—1379.42米。含大于0.30米的煤层35层,编号煤层为2l层,煤层平均总厚79.21来,按地层平均厚1045.61米计。含煤系数为7.6%。该组地层与下伏三叠系上统郝家沟组(T3h)呈平行不整合接触,与上覆三工河组(J1s)为整合接触。
根据以往物探及测井资料可知,该区地层电阻率在10~ 102.5Ω·m,其中以地表较为干燥的第四系覆盖层电阻率最高,达102.5Ω·m,以含水火烧区最最低约10Ω·m。而黑色泥岩以及泥质粉砂岩亦为低阻反应,以往电磁法勘探手段难以区分,往往根据电阻率绕曲及低阻圈闭并结合解释人员经验进行划分含水区边界,人为因素大,因此需要在资料解释阶段引入约束反演,提高资料解释的精细度。
2 工作方法及技术
瞬变电磁法(Transient electromagnetic method,TEM)属时间域电磁测深法,又称“纯异常场法”,它是利用阶跃波形电磁脉冲激发,利用不接地回线向地下发射一次场,在一次场的间歇期间(断电后),测量由地下介质产生的感应二次场随时间的变化来达到寻找各种地质目标体的一种引人注目的地球物理勘探方法。该方法对低阻反映灵敏、分层明显,是自八十年代在国内煤矿采空区探测、防治水等方面广泛应用并在近几年取得长足发展的煤矿物探新技术。
瞬变电磁法的工作原理是:在地表敷设不接地线框或接地电极,输入阶跃电流,当回线中电流突然断开时,在下半空间就要激励起感应涡流以维持断开电流前已存在的磁场,并且此涡流场随时间以等效涡流环的形式向下传播、向外扩展,利用不接地线圈、接地电极或地面中心探头观测此二次涡流磁场或电场的变化情况,用以研究浅层至中深层的地电结构。由于是在没有一次场背景的情形下观测纯二次场异常,因而异常更直接、探测效果更明显、原始数据的保真度更高。(其工作原理见右图)。
为了后期反演工作及三维解释的需要,本次试验采集按照40×40m的规则网度采集,采用大定源回线参数,共完成了5777点的原始资料采集。
资料处理方法
3.1预处理
对经过验收的原始资料进行滤波、排序等基础处理,为进一步的计算和处理工作做好准备。
瞬变电磁法观测数据是各测点各个延时(时窗)的瞬变感应电压,同一个测点不同延时(时窗)的感应电压不仅与某个深度的地层电阻率具有一定的相关性,而且和该深度上覆地层电阻率相关。
二次场归一化感应电压由于信号小,易受各种人文电磁、地表因素干扰,因此去除非地层电性产生的感应电压是瞬变电磁处理的首要目标。采用了直接的畸变数据剔除和非线性滤波两种方法。
瞬变电磁场法对于地表条件的适应性是比较强的,资料处理主要是针对电磁干扰的。对一些干扰大的测点先做单点平滑,然后再通过剖面图视电阻率等值线的形态进行分辨。一般来说,孤立的、非常密集的封闭圈往往不是真正的地质异常,需将其再次平滑。
当然,平滑的基础是受电磁干扰的瞬变实测衰减曲线仍保持了形态上的完整。为此,当干扰很大时除加大供电电流外(180-200A),每个测点上的重复观测次数多达7-8次直到获得较为理想的曲线为止。
3.2视电阻率计算
尽管感应电压高对应电阻率低,但不同时间的瞬变电磁二次场感应电压跨跃了5、6个数量级(甚至更大),而且不直观。将归一化瞬变感应电压换算成视电阻率、视纵向电导、视深度等直观参数是瞬变电磁数据处理不可缺少的,也是最基础的,它符合深度多少米电阻率多少的常规解释要求。几种主要参数计算公式如下
-------------------------晚期视电阻率 式中μ0=4π×107,M为发射磁矩M=I·L2,t为时窗时间,q为接收线圈的有效面积,VZ是感应电压
-----------------------纵向电导
------------------视深度 上述视电阻率、视深度是处理应得到的基本参数,根据资料的实际情况应进行滤波、优化反演等处理。
3.2 TEM大定源回线优化反演
建立如下目标函数ψ的模型,
式中,
,d是数据向量,m是模型向量,
是正演模拟函数,e是残差向量。其中
的分量
为
(归一化感应电动势,单位
);
为地电模型的电阻率向量,可令
为模型单元个数,且每一
为取对数后的电阻率值(即
)。正则化参数λ是一个正数。正定矩阵V起残差向量e之协方差的作用,其是数据误差的一种度量。ψ的第二项是为了获得稳定的解而对地电模型的一种约束。本程序将矩阵L取为简单的二阶微分算子,即Lm近似为Δ(
)。 非线性共轭梯度(NLCG)直接求解最小二乘的极小化问题,突破了
线性化迭代反演的框架。非线性共轭梯度的模型序列由一系列的一元极小化或沿着计算的搜索方向的线性搜索所确定,
搜索方向是对线性共轭梯度的近似,其迭代格式为,
式中,
。
成果解释
通过上述资料处理及优化反演,形成一个以40×40m为单元网格的三维数据体,并采用课题组自主开发的三维可视化解释软件,对该数据体按照解释资料形成剖面、水平切片以及联井剖面等,进行资料的最终解释,三维可视化效果如下图2,三维可视化效果图。资料解释过程中,采用该可视化软件可以根据需要叠加上已知的地质、钻孔、测井数据,形成地质、钻探、测井、瞬变电磁一体化的三维数据体,可对地下地质体完成初步的三维定位和显示,更好的提高解释精度及直观效果,极大的提高了解释效率。
本课题的研究区域内煤层较厚,各层煤都有燃烧,煤层的顶、底板比较破碎,火区地面塌陷严重。所以空区基本都有冒落现象,视电阻率剖面上的相对高阻对应着老窑和燃烧后形成的空区或者是这些区域冒落后形成的松散破碎带。相对低阻对应着火烧区含水体、老窑积水区、煤层燃烧区。在对异常体进行解释的时候,要在充分利用已知的地形地质资料的前提下,除视电阻率值的高低外,在判断异常方面还要考虑视电阻率等值线的形态、地形、地表电性不均匀程度、观测点原始数据质量等因素。
当然,实际的解释过程还是遵循有已知到未知,有剖面到平面的过程。其中下图3即为对验证钻孔部分局部放大的剖面显示。从图上可见,在标高500至900m,图形左侧小出现大面积低电阻率区,物探推测为火烧区含水体,与后期钻探验证情况完全吻合。
5.结论及建议
通过本次优化反演形成的瞬变电磁数据在低背景电阻率区域探测水区效果较好,能够在低电阻率的砂泥岩区见到较为明显的含水区边界,并经后期钻探验证,准确率较高;采用三维切片的方式使得解释过程更为直观、高效;反演过程中较好的利用了地质模型和综合测井资料,使得反演成果更为接近真实地质情况,有效的解决了瞬变电磁深度误差较大的问题。
由于本研究区后期发现浅部有大量的老窑采空区存在,在瞬变电磁资料上反应不明显,可见基于大定源回线的反演技术针对浅部(深度小于100m)低阻体探测存在一定的缺陷,使用过程中应结合浅层具体情况采用其他的方法进行补充。
参考文献:
[1]李貅,瞬变电磁测深的理论与应用,陕西科学技术出版社,2002。
作者简介:
苗圃(1967—)高级工程师,中国地质大学工程硕士学位,1990年工作,先后从事新疆煤田灭火处技术科科长、副总工程师、新疆煤炭科学研究所所长等工作。