2.5D controlled-source EM modeling with general 3D source geometries
2.5D controlled-source EM modeling with general 3D source geometries
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DOI：
10.1190/geo2011-0111.1
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发表时间：
2011-11
期刊：
影响因子：
3.3
通讯作者：
R. Streich;M. Becken;O. Ritter
中科院分区：
文献类型：
--
作者：
R. Streich;M. Becken;O. Ritter
迄今为止提出的大多数2.5D可控源电磁（CSEM）建模算法明确地只考虑平行或垂直于恒定电导率方向的点偶极子源。这使得复杂震源几何形状的模拟成本高昂，需要对许多点偶极子场进行单独评估，从而限制了此类方案在模拟和解释现场数据方面的实际适用性。我们提出了一种新的2.5D CSEM建模方案，克服了这一限制，并允许通过一次评估整个源的场来有效地模拟具有一般形状和方向的源。我们通过使用次级场方法来适应一般源，其中计算一般源和一维背景电导率模型的初级场。为了在空间和波数域之间进行所需的傅里叶变换，使用与传统算法相同的快速余弦和正弦变换滤波器，我们将主域和副域划分为对称和反对称部分。对于复杂的三维源几何形状，该方法明显比以前的2.5D算法更有效。我们的有限差分算法还包括低频散度校正和跨电导率不连续的电磁场插值的新方法。我们描述了建模方案，并通过将2.5 d模拟数据与1D和3D结果进行比较，证明了其准确性和效率。
Most 2.5D controlled-source electromagnetic (CSEM) modeling algorithms presented to date explicitly consider only sources that are point dipoles oriented parallel or perpendicular to the direction of constant conductivity. This makes simulations of complex source geometries expensive, requiring separate evaluations of many point dipole fields, and thus limits the practical applicability of such schemes for simulating and interpreting field data. We present a novel 2.5D CSEM modeling scheme that overcomes this limitation and permits efficient simulations of sources with general shape and orientation by evaluating fields for the entire source at once. We accommodate general sources by using a secondary field approach, in which primary fields are computed for the general source and a 1D background conductivity model. To carry out the required Fourier transforms between space and wavenumber domain using the same fast cosine and sine transform filters as in conventional algorithms, we split the primary and secondary fields into their symmetric and antisymmetric parts. For complex 3D source geometries, this approach is significantly more efficient than previous 2.5D algorithms. Our finite-difference algorithm also includes novel approaches for divergence correction at low frequencies and EM field interpolation across conductivity discontinuities. We describe the modeling scheme and demonstrate its accuracy and efficiency by comparisons of 2.5D-simulated data with 1D and 3D results.