提高测井曲线纵向分辨率的方法

常规处理方法往往漏掉一些有价值的薄油气储层。利用频率域反槽积方法、贝叶斯反褶积方法、反褶积与光滑滤波组合（ＤＦＳＮ）方法和分辨率匹配与非线性拟合方法对测井曲线进行了提高纵向分辨率处理，测井曲线的纵向分辨率可提高１～４倍，一些结果得到了证实，为准确地定量评价薄储居提供了较可靠的参数     

基于方向tilt-Euler的三维磁数据快速反演

三维磁异常快速反演是磁法勘探进行地质解释的一项重要内容.本文在方向tilt梯度基础上进行导数处理,并进行合理改进,得到了6个改进的方向tilt梯度导数,丰富了不同方向上的磁异常信息.对常规欧拉反褶积方程进行三个方向求导,所构成的方程组与6个改进的方向tilt梯度导数进行结合,从而构建出了两个基于方向tilt梯度导数的快速反演方程组（方向tilt-Euler法）,用于反演场源的位置参数.另外,将三个方向导数下的欧拉反褶积进行平方和及均方根处理,得到了场源构造指数的求解公式.单一模型试验表明,6个改进的方向tilt梯度导数异常基本不受磁化方向影响,可从不同方向上反映磁异常信息,方向tilt-Euler能够准确地反演出场源的位置及构造指数.叠加模型试验证实了方向tilt-Euler法相对于tilt-Euler法,具有反演解聚集度更强、连续性更好、反演准确度更高、受噪声影响更小及无虚假反演解等优点.将本文方法应用于内蒙古塔木素航磁资料处理中,获得了丰富的地下磁源分布信息,为了解该地区隐伏断裂构造及岩体分布等提供了有效依据.

     

基于欧拉反褶积法的无人机航磁找矿应用

无人机航磁测量以其高效、安全、低成本等优点逐渐应用到中小面积大比例尺资源勘探领域。本文针对安徽芜湖市三山区22 km²区域构造刻画和找矿前景预测,开展1∶20 000高精度无人机航磁测量工作;推导了欧拉反演求解过程,并分析对比构造指数选取,使用构造指数为0的欧拉反褶积对航磁数据进行反演求解,获得地下磁异常体构造边界解集信息;将其应用到研究区域航磁数据反演,根据反演得到的边界位置和深度信息圈定了18处断裂,并结合异常特征给出了8.7 km²岩浆岩分布区,根据宁芜区域铁矿成矿特点,圈定岩浆分布区及边界为成矿详查区。     

VSP资料约束地层反滤波研究

浅地表的低速带和地层滤波作用导致地震信号的能量衰减,地震子波的高频快速衰减,速度频散的子波变形,对地震底层分析带来了严重的影响。地层反滤波算法就是为了消除地层对子波的影响,利用VSP中的直达下行波推算出每个地层滤波算子,计算出各个地层滤波算子的反算子,然后利用这些反算子恢复出地表记录中损失掉的高频成分,减弱地层滤波对波形的影响,增加地表记录的频率成分和波形的准确度。分析实际地震资料表明,经过地层反滤波处理后的记录频率成分明显提升,地质构造更加准确、清晰。     

航磁梯度数据解释新方法在迁安铁矿勘探中的应用

为更加清晰和准确地利用磁梯度数据获得地质体的分布特征,笔者采用解析信号总水平导数法和梯度欧拉反褶积技术组合实现磁梯度数据的解释,解析信号总水平导数的极值可有效地圈定出矿体的分布范围,梯度欧拉反褶积法可有效地避免背景异常的干扰,从而准确地给出磁性体的位置和深度信息。理论模型证明解析信号水平导数法和梯度欧拉反褶积法的组合可准确地获得磁性体的水平范围和深度。应用于河北迁安地区磁梯度数据的解释,圈定出5个呈条带状分布的较大型铁矿藏,埋深在200~450 m。     

一种改进的基于非高斯性最大化的预测反褶积算法

The predictive deconvolution algorithm （PD）, which is based on second-order statistics, assumes that the primaries and the multiples are implicitly orthogonal. However, the seismic data usually do not satisfy this assumption in practice. Since the seismic data （primaries and multiples） have a non-Gaussian distribution, in this paper we present an improved predictive deconvolution algorithm （IPD） by maximizing the non-Gaussianity of the recovered primaries. Applications of the IPD method on synthetic and real seismic datasets show that the proposed method obtains promising results.     

Nonstationary deconvolution using maximum kurtosis optimization

Deconvolution is an essential step for high-resolution imaging in seismic data processing. The frequency and phase of the seismic wavelet change through time during wave propagation as a consequence of seismic absorption. Therefore, wavelet estimation is the most vital step of deconvolution, which plays the main role in seismic processing and inversion. Gabor deconvolution is an effective method to eliminate attenuation effects. Since Gabor transform does not prepare the information about the phase, minimum-phase assumption is usually supposed to estimate the phase of the wavelet. This manner does not return the optimum response where the source wavelet would be dominantly a mixed phase. We used the kurtosis maximization algorithm to estimate the phase of the wavelet. First, we removed the attenuation effect in the Gabor domain and computed the amplitude spectrum of the source wavelet; then, we rotated the seismic trace with a constant phase to reach the maximum kurtosis. This procedure was repeated in moving windows to obtain the time-varying phase changes. After that, the propagating wavelet was generated to solve the inversion problem of the convolutional model. We showed that the assumption of minimum phase does not reflect a suitable response in the case of mixed-phase wavelets. Application of this algorithm on synthetic and real data shows that subtle reflectivity information could be recovered and vertical seismic resolution is significantly improved.     

Deconvolution of teleseismic recordings for mantle structure

Delineation of detailed mantle structure frequently requires the separation of source signature and structural response from seismograms recorded at teleseismic distances. This deconvolution problem can be posed in a log-spectral domain where the operation of time-domain convolution is reduced to an additive form. The introduction of multiple events recorded at many stations leads to a system of consistency equations that must be honoured by both the source time functions and the impulse responses associated with propagation paths between sources and receivers. The system is inherently singular, and stabilization is accomplished through the supply of an initial estimate of the source time function. Although alternative choices exist, an effective estimate is derived from the eigenimage associated with the largest eigenvalue in a singular-value decomposition of the suite of aligned seismograms corresponding to a given event. The relation of the deconvolution scheme to simultaneous least-squares deconvolution is examined. Application of the methodology to broadband teleseismic P waveforms recorded on the Canadian National Seismograph Network demonstrates the retrieval of effective Green's functions including secondary phases associated with upper-mantle structure.