LWD声频数据处理在慢速地层高质量剪切慢度测井中的应用

Ruijia Wang, Jiajun Zhao, Taher A. Kortam
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引用次数: 0

摘要

对于随钻测井(LWD)或电缆环境中的常规单极声源,剪切慢度测井很难获得,特别是在通常没有直接折射剪切波到达的缓慢地层中。对于LWD偶极子源,地层挠曲波通常与最低阶的工具挠曲波耦合,因此挠曲模式在低频时不接近横波慢度。从随钻偶极子数据中提取剪切慢度需要进行色散校正。相反,产生螺旋波的四极杆点火被认为是用于剪切测量的最佳LWD激励模式。螺旋波在随钻测井环境中的一个基本特征是,其非泄漏截止频率慢度是地层剪切慢度。然而,随钻螺旋波截止频率附近的慢度数据由于激发幅值较低,往往受到噪声或其他模态的影响。为了克服这些随钻测井数据处理的挑战,我们提出了一种数据驱动的处理方法,该方法利用了频域中现有模式的所有有用的色散响应。该方法首先生成一个差分相位频率-慢度相干图,并提取慢度色散与频率的关系。然后,它计算慢度密度对数,参考沿慢度轴的色散响应的强度。接下来,应用边缘检测方法捕获慢度密度图上与剪切慢度相关的第一个峰值的边缘。为了完善剪切慢度的答案,剪切慢度的初始估计作为另一种算法的输入,该算法最大限度地减少螺旋慢度矢量与简化的螺旋离散模型之间的不拟合。简化的螺旋色散模型由一个预先计算的理论螺旋色散曲线库和两个数据驱动参数组成。测量数据使用这两个数据驱动参数分别在频率轴和慢度轴上拉伸基本色散模型,以解释由变化、各向异性或其他未包含在正演建模中的参数产生的误差。该方法也可应用于弯曲波,即从经过频散校正处理的弯曲波慢度密度图中提取剪切慢度的初始猜测值。本文介绍了软地层中井眼弯曲波和螺旋波处理的实例研究。采用改进的差相频率相似(MDPFS)方法从实测波形中提取模态波的全频色散响应。将数据驱动的剪切慢度处理应用于色散响应。对偶极弯曲波和四极螺旋波进行了处理。弯曲或螺旋波慢度的慢度密度对数和色散校正慢度的组合被用作最终估计剪切的QC度量。结果表明,即使剪切慢度高达500s/ft, LWD声波工具也能很好地测量弯曲和螺杆分散。从弯曲波和螺旋波中提取的剪切慢度与有线剪切慢度测井曲线吻合良好,证明了处理的可靠性和鲁棒性。
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APPLICATION OF LWD ACOUSTIC DISPERSIVE DATA PROCESSING FOR HIGH-QUALITY SHEAR SLOWNESS LOGS IN SLOW FORMATIONS
For conventional acoustic monopole sources in a logging-while-drilling (LWD) or wireline environment, shear slowness logs can be hard to obtain, particularly in slow formations where direct refracted shear-wave arrivals are often absent. For LWD dipole sources, formation flexural waves are often coupled with the lowest order of tool flexural waves, so the flexural mode does not approach shear wave slowness at low frequencies. A dispersion correction is required to extract shear slowness from LWD dipole data. Instead, a quadrupole firing, which generates screw waves, is considered the best LWD excitation mode for shear measurement. A fundamental feature of screw waves in an LWD environment is that their non-leaky cutoff frequency slowness is the formation shear slowness. However, slowness data near the cutoff frequency of LWD screw waves are often influenced by noise or the presence of other modes because of low excitation amplitude. To overcome these LWD data processing challenges, we propose a data-driven processing method that uses all useful dispersion responses of existing modes in the frequency domain. The process first generates a differential phase frequency-slowness coherence map and extracts the slowness dispersion vs. frequency. Then, it computes the slowness density log, referring to the intensity of the dispersion response along the slowness axis. Next, an edge-detection method is applied to capture the edge of the first peak associated with shear slowness on the slowness density map. To refine the shear slowness answer, this initial estimate of shear slowness serves as the input to another algorithm that minimizes the misfit between the screw slowness vector and a simplified screw dispersion model. The simplified screw dispersion model consists of a pre-computed base library of theoretical screw dispersion curves and two data-driven parameters. The two data-driven parameters are used by the measured data to stretch the base dispersion model in the frequency and slowness axes, respectively, to account for errors generated by alteration, anisotropy, or other parameters not included in the forward modeling. The method can also be applied to flexural waves, where the initial guess of shear slowness is picked from the slowness density map of flexural waves after dispersion-correction processing. This paper shows a case study of borehole flexural and screw waves processing in soft formations. A modified differential-phase frequency-semblance (MDPFS) approach is applied to extract the mode waves' full-frequency dispersion response from measured waveforms. The data-driven shear slowness processing is applied to the dispersion response. Both dipole flexural waves and quadrupole screw waves are processed. A combination of slowness density log from the flexural or screw wave slowness and the dispersion-corrected slowness is used as a QC metric of the final estimated shear. Results show that flexural and screw dispersions are well measured by the LWD sonic tool, even if the shear slowness is as large as 500 s/ft. Shear slowness extracted from flexural waves and screw waves match well with each other and with wireline shear slowness logs, demonstrating that the processing is reliable and robust.
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