2019年4月

探索中有哪些新内容?

跳出[冰]盒子思考
威廉(比尔)负责人/特约编辑

我最近参加了在德克萨斯州纳科多奇斯举行的美国物理教师协会 (AAPT) 德克萨斯州春季会议,该会议由物理学生协会 (SPS)、美国物理学会德克萨斯分会和 AAPT 德克萨斯分会部分赞助。20 世纪 60 年代末,SPS 的绰号让我在芝加哥遇到了一些麻烦。与一位身为富布赖特学者的物理老师结婚,就能解释剩下的事情。

激光雷达技术。 我听取了关于激光雷达技术的演示,该技术用于测量冰晶的单散射特性,建模为水平板和垂直柱(Saito 和 Yang,[德克萨斯 A&M],“水平定向冰晶的相矩阵及其在大气中的应用”)科学,”2019 年,海报,TS-AAPT,斯蒂芬·F·奥斯汀州立大学。)

我和斋藤愉快地交流了相互调查的知识。激光雷达是一种单激光源、单接收器成像设备,我们在行业研究中使用它对海底石油结构进行成像,以确定安全问题(如果有)。研究人员还希望有一天将激光雷达应用到深水中。然而,虽然激光雷达需要进行多次扫描,并且一些设备作为阵列运行(对于激光波长来说是巨大的),但它仍然是一种原始的二维单反射器成像仪,大约相当于医院的 MRI。 

海洋工程师正在努力将激光雷达工具的多向通道组合成可用的 3D 彩色图像,这比医生的黑白剥离图片要好得多 [请参阅深度 3D]。用于油田应用的地震图像信号技术比激光雷达领先数光年。与地震处理器一样,Saito 使用麦克斯韦方程将激光束一维标量反射的远场散射与近场散射分开。麦克斯韦方程是一组偏微分方程,连同一组关于表面信号/反射行为的假设,以数学方式描述了物理边界处的源和接收器限制。有趣的是,齐藤在他对水平和垂直散射的严格假设中发现了相位差。地震反射的相变对于勘探很重要。深入分析他的解决方法可能会有用。

矢量球面波函数。 第二张海报由 Jiachen Ding、P. Yang 提出,将激光散射概念引入矢量空间。“计算非球形介电粒子光散射时不变嵌入 T 矩阵方法的收敛”,同上。丁博士正在研究反射信号的内部数学变换特性,使用“矢量球面波函数”。这里的球面波传播类似,但与地震反射理论并不完全相同。然而,丁的模型是从反射颗粒尺寸和形状的假设开始的。他的工作是尝试应用甚高频返回信号来迭代求解颗粒形状、折射率和尺寸。这可能是快速计算处理的另一种方法,以消除电磁和微震中发现的大数据集中的“地质噪声”。 

北极应用。 另一篇论文涉及北极应用,我将其与探索新海洋盆地区域的可能的环境去/不去决策联系起来(Bell、Yang [德克萨斯农工大学]、Wu [美国宇航局],“了解亚毫米波长冰云特性检索”混合相云的存在,”同上)。 

对冰颗粒的大小和形状进行了假设,并在信号的显着散射范围内创建了红外图像起源的流动模型,该信号现在通常用于确定大气中的冰并计算地球的辐射。监管机构使用的“预算”, 图 1。 贝尔还没有数据可供比较,只是根据一系列假设进行的模拟。为什么?当今北极上空冰云的准确信息是单信号的,假设所有反射数据都是由均匀的单层云创建的。你曾经到过北方的水面吗?水面上只有一层云的情况很少见。根据卫星的冰预测,在谴责北纬 66°33”47.5”以北的活动之前,我们需要进行更多的研究。

图 1:美国宇航局兰利分校研究员帕特里克·泰勒发现,云和海冰对北极气候变化的影响可能比之前想象的更为复杂。 图片:美国宇航局
图 1:美国宇航局兰利分校研究员帕特里克·泰勒发现,云和海冰对北极气候变化的影响可能比之前想象的更为复杂。图片:美国宇航局

 

贝尔博士表示,他的模型中最关心的是冰颗粒形状和冰颗粒有效直径的假设。该模型难以校准,采用亚毫米波长技术。这听起来就像岩石物理学大师 Mavko、Mukerji 和 Dvorkin 在为微观层面上存在的各种形状的孔隙度周围的岩石颗粒的大小和形状选择模型时所经历的斗争,这些孔隙度存在于相当不均匀的储层子矩阵中,但用宏观工具(参见 《岩石物理手册:多孔介质地震分析工具》, 剑桥大学出版社,2013 年)。 

演讲者曾经接受过石油和天然气应用方面的培训,他们受到鼓舞,甚至热衷于尝试他们的新世界解决方案。

关于作者
威廉·(比尔)·海德
特约编辑
William (Bill) Head 是一位技术专家,在美国和国际勘探领域拥有 40 多年的经验。
相关文章 来自档案
原文链接/worldoil
April 2019
Columns

What's new in exploration?

Think outside the [ice] box
William (Bill) Head / Contributing Editor

I recently attended the American Association of Physics Teachers’ (AAPT) Texas Spring Meeting in Nacogdoches, Texas, sponsored in part by the Society of Physics Students (SPS), The Texas Section of the American Physical Society, and the Texas Section of AAPT. The SPS moniker got me into some trouble in Chicago in the late 1960s.  Marrying a physics teacher, who is a Fulbright Scholar, explains the rest.

Lidar technology. I listened to a presentation about Lidar technology to measure single-scattering properties of ice crystals, modeled as both horizontal plates and vertical columns (Saito and Yang, [Texas A&M], “Phase Matrices of Horizontally Oriented Ice Crystals and Their Applications in Atmospheric Sciences,” 2019, Poster, TS-AAPT, Stephen F. Austin State University.)

Saito and I were able to have fun exchanging knowledge of mutual investigations. Lidar is a single-laser source, single-receiver imaging device that we use in industry research to image subsea oil structures, to determine safety issues, if any. Research also wants to apply Lidar into deep water someday. However, while Lidar takes multiple scans, and some equipment operates as an array (huge for laser wavelengths) it is still a primitive, two-dimensional, one-reflector imager, about equal to your hospital’s MRI. 

Marine engineers are working on combining multi-directional passes of the Lidar tool into a usable 3D color image, much better than your doctor’s B&W stripped picture [see 3D at Depth]. Seismic-image signal technology for oil field application is light years ahead of Lidar. Like seismic processors, Saito is using Maxwell’s equations to separate far-field scatter from near-field scatter of the one-dimensional, scalar reflection of the laser beam.  Maxwell’s equations are a set of partial differential equations that, along with a set of assumptions about signal/reflective behavior at surfaces, describe mathematically source and receiver limits at physical boundaries. What is interesting is that Saito found phase differences in his strict assumptions of horizontal and vertical scatter. Phase change in seismic reflection for exploration is important. Digging into analysis of his solution method might be useful.

Vector spherical wave function. A second poster by Jiachen Ding, P. Yang, takes the laser scattering concept into vector space. “On the Convergence of Invariant Imbedding T-matrix Method in Computing Light scattering by Nonspherical Dielectric Particles,” ibid. Dr. Ding was examining the internal math of reflected signal for properties of transformation, using a “vector spherical wave function.” Spherical wave spreading here is similar, but not quite identical to seismic reflection theory. However, Ding’s model starts with assumptions of reflected particle size and shape. His work is an attempt to apply very high-frequency returned signal to iterate toward a solution of particle shape, refractive index and size. This may be an alternate way to fast compute processing to eliminate “non-geologic noise” from within large data sets found in EM and microseismic. 

Arctic applications. Another paper dealt with Arctic applications that I link to possible environmental go/no-go decisions to explore new marine basinal areas (Bell, Yang [Texas A&M], Wu [NASA], “Understanding sub-millimeter wavelength ice cloud property retrievals in the presence of mix phase clouds,” ibid). 

Assumptions were made about the size and shape of ice particles, and creating a flow model of just where infrared images originate from, within the significant scattering of signal now being used commonly to determine ice in the atmosphere and to calculate the Earth’s radiation “budget,” as used by regulators, Fig. 1Bell also has no data, yet, to compare, just simulations from a series of assumptions. Why?  Accurate information about ice clouds over the Arctic today are mono-signal, assumptive that all reflective data are created from a homogeneous, single-layer cloud. Have you ever been up north over the water? A single cloud layer over that water is rarely the case. We need a lot more studies before condemning activity north of latitude 66°33′47.5″ N, based on ice predictions from satellites.

Fig. 1. NASA-Langley researcher Patrick Taylor finds that the role of clouds and sea ice for Arctic climate change may be more complex than previously thought. Image: NASA
Fig. 1. NASA-Langley researcher Patrick Taylor finds that the role of clouds and sea ice for Arctic climate change may be more complex than previously thought. Image: NASA

 

Dr. Bell stated that his greatest concern in his model was the assumption of shapes of ice particles, and ice particle effective diameter. The model, difficult to calibrate, uses sub-mm wavelength technology. This sounds like the struggles that rock physics gurus Mavko, Mukerji and Dvorkin have in picking models for both size and shape of rock particles surrounding various shapes of porosity present on a micro level, in rather non-homogenous sub-matrices of reservoirs but measured with macro tools (see The Rock Physics Handbook: Tools for Seismic Analysis of Porous Media, Cambridge University Press, 2013). 

The presenters, once coached about oil and gas applications, were encouraged and maybe even enthusiastic about trying their solutions to a new world—ours. WO

About the Authors
William (Bill) Head
Contributing Editor
William (Bill) Head is a technologist with over 40 years of experience in U.S. and international exploration.
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