The Gravity Module Assembly used in airborne full tensor gradiometry surveys

In airborne gravity gradiometry, the Gravity Module Assembly is an optional gravimeter unit that is mounted on the same stabilized platform as the Full Tensor Gradiometer. Direct measurements of the gravity field are needed from this device to constrain the long wavelengths when gradient data are integrated mathematically to form high-resolution gravity fields. The Gravity Module Assembly is, however, capable of providing independent gravity data with a specification approaching that expected from a dedicated airborne gravity system. Presented here is an error analysis of data from this instrument collected alongside the Full Tensor Gradiometer during an airborne survey. By having both gradiometry and gravity datasets, comparisons of the information content in these two types of measurement are made.     

沙漠地区地震勘探随机噪声建模及其在噪声压制中的应用

随机噪声是影响地震勘探有效信号的主要因素,其存在大大降低了地震记录的信噪比.在噪声压制方法不断被改进的同时,对随机噪声特性进行研究,了解噪声的产生机制是对其进行压制的先决条件,目前对噪声的研究主要是特性研究以寻找规律性,对其进行定性定量的分析还比较少.本文根据塔里木沙漠地区实际采集环境,考虑到噪声的连续性给计算带来的不便,假设各类噪声源以点源的形式分布在检波器周围,依据相应理论确定各类噪声源的源函数,其激发的噪声经由波动方程传播,将随机噪声作为各类噪声源共同作用的综合波场,建立随机噪声的理论模型.通过分析不同种噪声对地震记录的影响,选取合适的滤波方法对其进行压制,实验结果表明,通过建立沙漠地区随机噪声的理论模型,为选择有效的滤波方法,提高地震记录信噪比起到理论指导作用.     

基于能量运算的磁共振信号尖峰噪声抑制方法

磁共振探测信号微弱,使用高灵敏度的核磁共振地下水探测仪,极易受到环境噪声干扰.其中,工频谐波噪声和尖峰噪声,是影响信号质量最严重的两类噪声.国内外研究表明,通过参考线圈的布设,依据探测线圈和参考线圈中噪声相关性,利用自适应参考对消算法,能够有效抑制工频谐波噪声.然而,尖峰噪声的存在严重影响了主通道与参考道的数据相关性,成为了参考对消算法应用的难题与障碍.为解决这一问题,本文提出磁共振信号中尖峰噪声的抑制方法,推导了能量域磁共振信号表达式,通过计算信号能量,可有效检测尖峰噪声并突出不易识别的小幅度尖峰噪声,采用基于中位数的绝对偏差法确定阈值,进而剔除尖峰噪声.为了验证去噪效果,与应用较广的统计叠加法进行对比研究.仿真结果表明,对于干扰幅度较大、持续时间较长的尖峰噪声,能量运算法和统计叠加法均能识别并剔除,且不损失有效的磁共振信号,标准差偏差控制在0.3%以内,可以满足实际应用的要求;对于小于信号幅度1.5倍的尖峰噪声,能量运算法可有效识别并剔除,而统计叠加法无法实现.针对多通道探测系统,使用能量运算法剔除尖峰噪声后,可明显提高主通道和参考道的数据相关性,为后续自适应参考对消算法的应用奠定了基础.实测数据处理结果进一步证明了本文方法的实用性.     

The utilization of the double focal transformation for sparse data representation and data reconstruction

In many cases, seismic measurements are coarsely sampled in at least one dimension. This leads to aliasing artefacts and therefore to problems in the subsequent processing steps. To avoid this, seismic data reconstruction can be applied in advance. The success and reliability of reconstruction methods are dependent on the assumptions they make on the data. In many cases, wavefields are assumed to (locally) have a linear space–time behaviour. However, field data are usually complex, with strongly curved events. Therefore, in this paper, we propose the double focal transformation as an efficient way for complex data reconstruction. Hereby, wavefield propagation is formulated as a transformation, where one‐way propagation operators are used as its basis functions. These wavefield operators can be based on a macro velocity model, which allows our method to use prior information in order to make the data decomposition more effective. The basic principle of the double focal transformation is to focus seismic energy along source and receiver coordinates simultaneously. The seismic data are represented by a number of localized events in the focal domain, whereas aliasing noise spreads out. By imposing a sparse solution in the focal domain, aliasing noise is suppressed, and data reconstruction beyond aliasing is achieved. To facilitate the process, only a few effective depth levels need to be included, preferably along the major boundaries in the data, from which the propagation operators can be calculated. Results on 2D and 3D synthetic data illustrate the method's virtues. Furthermore, seismic data reconstruction on a 2D field dataset with gaps and aliased source spacing demonstrates the strength of the double focal transformation, particularly for near‐offset reflections with strong curvature and for diffractions.     

GNMF小波谱分离在地震勘探噪声压制中的应用

地震勘探资料噪声压制及信噪比提高是整个地震勘探信号处理过程中的重要任务,随着地震勘探深度的增加及其复杂性,人们对地震数据质量的要求越来越高.勘探环境的复杂化使得采集到的地震资料中有效信号被大量噪声淹没,无法清晰辨识,严重影响后续的数据处理与解释.小波去噪是地震勘探中常用且发展较成熟的一种方法,但是其涉及到的阈值函数选取问题一直令人困扰,虽然已有多种阈值函数被提出,但仍存在各自的缺陷.本文利用小波分解在时域及频域良好的信号细节体现特性,引入模式识别中的非负矩阵分解(NMF)谱分离思想,针对小波系数阈值优化问题,提出了一种小波域图非负矩阵分解(GNMF)消噪算法.该方法首先在小波分解基础上,利用GNMF算法实现小波分解系数谱中信号分量与噪声分量的谱分离,然后通过反变换重构各分离子谱对应的子信号,最后利用K均值聚类算法将得到的多个子信号划分为信号类及噪声类,最终得到重构信号及分离噪声.合成记录和实际地震资料的消噪结果验证了新方法在提高信号与噪声分离准确性和精度方面的有效性,同时新方法避免了阈值选取造成的噪声压制不理想或有效成分损失问题.与小波消噪结果的对比及数值分析也说明了新方法在噪声压制及有效成分保持方面的优势.     

Scattered ground‐roll attenuation using model‐driven interferometry

Scattered ground roll is a type of noise observed in land seismic data that can be particularly difficult to suppress. Typically, this type of noise cannot be removed using conventional velocity‐based filters. In this paper, we discuss a model‐driven form of seismic interferometry that allows suppression of scattered ground‐roll noise in land seismic data. The conventional cross‐correlate and stack interferometry approach results in scattered noise estimates between two receiver locations (i.e. as if one of the receivers had been replaced by a source). For noise suppression, this requires that each source we wish to attenuate the noise from is co‐located with a receiver. The model‐driven form differs, as the use of a simple model in place of one of the inputs for interferometry allows the scattered noise estimate to be made between a source and a receiver. This allows the method to be more flexible, as co‐location of sources and receivers is not required, and the method can be applied to data sets with a variety of different acquisition geometries. A simple plane‐wave model is used, allowing the method to remain relatively data driven, with weighting factors for the plane waves determined using a least‐squares solution. Using a number of both synthetic and real two‐dimensional (2D) and three‐dimensional (3D) land seismic data sets, we show that this model‐driven approach provides effective results, allowing suppression of scattered ground‐roll noise without having an adverse effect on the underlying signal.     

Gravimetric monitoring of the first field‐wide steam injection in a fractured carbonate field in Oman – a feasibility study

Gas‐Oil Gravity Drainage is to be enhanced by steam injection in a highly fractured, low permeability carbonate field in Oman. Following a successful pilot, field‐wide steam injection is being implemented, first of this type in the world. A dedicated monitoring program has been designed to track changes in the reservoir. Various observations are to be acquired, including, surface deformation, temperature measurements, microseismic, well logs, pressure and saturation measurements to monitor the reservoir. Because significant changes in the reservoir density are expected, time‐lapse gravimetry is also being considered. In this paper we investigate the feasibility of gravimetric monitoring of the thermally enhanced gravity drainage process at the carbonate field in Oman. For this purpose, forward gravity modelling is performed. Based on field groundwater measurements, the estimates of the hydrological signal are considered and it is investigated under what conditions the groundwater influences can be minimized. Using regularized inversion of synthetic gravity data, we analyse the achievable accuracy of heat‐front position estimates. In case of large groundwater variations at the field, the gravity observations can be significantly affected and, consequently, the accuracy of heat‐front monitoring can be deteriorated. We show that, by applying gravity corrections based on local observations of groundwater, the hydrological influences can to a large extent be reduced and the accuracy of estimates can be improved. We conclude that gravimetric monitoring of the heat‐front evolution has a great potential.     

岩石力学参数对裂缝发育程度的影响

弹性模量(E)、泊松比(μ)及密度(ρ)是岩石的重要力学参数, 当其他条件一致时, 在一定程度上影响着裂缝的发育。以塔里木盆地某气田为研究区, 在造缝期古应力场分析的基础上, 利用储层裂缝数值模拟技术, 计算得到储层裂缝孔隙度; 再以裂缝孔隙度为指标, 分析岩石力学参数对裂缝发育程度的影响。研究结果表明, 裂缝孔隙度随弹性模量的增加而增大, 同等应力条件下, 弹性模量越大, 裂缝孔隙度越高, 破裂程度越大; 泊松比小于0.2时, 裂缝孔隙度随泊松比增加而逐渐下降; 泊松比超过0.2后, 裂缝孔隙度随泊松比增加而逐渐增大; 岩石密度对裂缝孔隙度的影响不大, 基本上可以忽略。      

加卸载响应比的新进展

本文对此作简要介绍。主要有下三方面：①预测效果好：2004年发生在中国大陆有资料地区的ML≥15级地震共17次,其中15次落入用加卸载响应比方法于2003年底预测的区域内。②通过大量基础研究(包括数值模拟,岩石力学实验及统计细观损伤力学研究),使加卸载响应比理论(LURR)建立在一个比较牢靠的科学基础上。③LURR有很大的潜力和发展空间。未来的发展空间,除预测天然地震外,还可能对矿震、水库地震、滑坡等自然灾害,甚至其它自然系统以致社会系统的灾变作出预测。     

高阶统计量在大地电磁测深数据处理中的应用研究

在大地电磁（MT）测深法中,大地电磁响应函数经常出现个别频点分散、误差棒较大、形态异常等现象,在作反演解释时,许多地质特征难以有效提取出来,这些问题严重阻碍了MT的实际应用效能和发展.本文利用高阶统计量方法检验了MT信号的高斯性. 结果表明,MT信号是非高斯的. 根据任何高斯过程,其高阶统计量（高阶累积量,高阶谱）均为零的性质,通过信号的高阶谱恢复功率谱,再由功率谱估算MT响应函数,能有效抑制高斯有色噪声的影响,提高MT资料的处理质量. 从应用效果看,这种方法在抑制高斯有色噪声、提取信号中有用信息方面优于传统功率谱方法.