微地震速度模型和高精度定位贝叶斯反演方法

微地震监测技术是评估非常规油气水力压裂裂缝发展的重要手段。速度模
型的准确性对微地震成像结果起着举足轻重的作用。传统方法根据声波测井信
号建立初始模型，然后利用射孔事件信息进一步优化速度模型。该方法受限于
射孔事件个数较少和射线路径覆盖范围较窄，反演过程中稳定性较差，遇到复
杂地层时反演误差较大，严重影响微地震事件定位精度。为了提高微地震事件
定位准确度，本文在利用微地震信号约束反演过程的基础上，以灵活优化速度
模型的层位结构和速度值为出发点，探讨了复杂地质条件下的速度模型校正方
法和微地震事件定位精度提升手段，并致力于满足实际微地震监测的需求，主
要获得了以下几个成果：
针对复杂地质条件下初始速度模型误差较大、微地震事件定位精度较差的
难题，本文首次将贝叶斯变维方法应用于井中速度模型校正，反演过程中同时
优化速度模型的层位个数、深度以及各层速度值，在射孔事件和微地震事件等
有效信号的约束下，获得稀疏的等效速度模型。理论和实际数据应用均表明，
该方法受声波测井信息影响较小，可以有效提高微地震事件定位精度。
速度模型和微地震事件位置联合反演存在折衷风险，为了防止微地震事件
定位结果出现系统偏差，本文将主事件定位方法和贝叶斯速度参数推导方法相
结合，提出了增量虚拟主事件(IPM)方法。IPM 方法迭代优化微地震事件位置和
速度模型精度，减少了反演参数个数，保证反演稳定性。理论和实际数据应用
均表明，IPM 方法适用于不同地质条件速度模型优化，成倍级减小了微地震事
件定位偏差。
当遇到水力压裂地区存在强各向异性特征严重影响微地震事件定位精度时，
本文基于IPM 方法推断了VTI 介质各向异性参数。在固定维反演测试中，IPM
方法定量预测了各向异性参数的不确定性。在变维反演测试中，IPM 方法成功
获得稀疏的等效各向异性速度模型，减少了微地震事件定位偏差。
针对贝叶斯反演中应用MCMC 采样方法需要多次迭代、影响计算速率的问
题，本文结合打靶法原理简单和最短路径法对速度结构适用性强的特点，开发
了适于多个检波器走时快速计算的各向同性和VTI 介质射线追踪算法。该算法简洁高效，
用稀疏的节点推断出高精度的走时和射线路径，有助于提升速度模
型反演效率，便于实时定位。
本文提出的速度校正方法克服了传统方法约束信息少、速度模型适用性差、
定位误差大、反演效率低的问题，适用于复杂地质条件下的微地震监测，减少
了微地震事件定位偏差到十米量级，反演效率提升了数十倍。适合于实际水力
压裂生产，为提高非常规能源油气采收率提供了有效的保障。

Microseismic monitoring technology has become one of the most important
methods to evaluate hydraulic fracturing in unconventional oil and gas exploitation.
The velocity model in downhole monitoring has a serious effect on the accuracy of
the microseismic image. In the traditional method, the initial velocity model is
established based on acoustic logging signals, and then the velocity model is further
optimized by using the perforation shot information. Due to the limited number of
perforation shots and narrow coverage of ray paths, this method has poor stability in
the inversion process, and it may cause large event location errors in microsei smic
monitoring in complex formations. It is difficult to accurately describe the fracture
morphology of hydraulic fracturing. To improve the location accuracy of
microseismic events, we introduced more effective constraints with the microseismic
events to the velocity optimization. To get a flexible velocity model structure and
improve the event location accuracy, we carefully discussed the velocity optimization
method in complex geological conditions. Also, it was committed to meeting the
needs of field microseismic monitoring. The main achievements are as follows:
To solve the problem of large initial velocity model error and low event location
accuracy under complicated geological conditions, we first introduced the Bayesian
transdimensional inversion to downhole velocity calibration. During the inv ersion
process, the layer number, the layer depths, and the velocity values were updated
simultaneously, and finally a sparse velocity model was obtained under the constraint
of the perforation shots and microseismic events. Both theoretical and field examples
showed that our method was less affected by acoustic logging information, and the
location accuracy of the microseismic events can be effectively improved.
The simultaneous inversion of velocity model and microseismic event location s
still faces the risk of coupling on the condition of fitting the observed travel times,
some systematic deviations may be unavoidable. To avoid the errors in microseismic
event location results, an Incremental Pseudo-Master (IPM) method was proposed in
this paper. It combines the advantage of the master-event location method and the
Bayesian inference. In the IPM method, the accuracy of the microseismic event
locations and the velocity model were iteratively improved, and the number of model
parameters was reduced to improve the inversion stability. The synthetic and field tests all represented that the IPM method was suitable for velocity optimization under
different geological conditions, and the microseismic event location accuracy can be
largely improved.
When the strong anisotropy in the hydraulic fracturing area seriously affects the
location accuracy of the microseismic events, we deduced the anisotropy parameters
of VTI (Vertical Transverse Isotropy) media based on the IPM method. In the fixed
dimensional inversion, the IPM method successfully predicted the uncertainty of the
anisotropic parameters. In the transdimensional inversion, the IPM method
successfully obtained the sparse equivalent anisotropic velocity model, which
effectively improved the location accuracy of the microseismic events.
To solve the problem that the MCMC (Markov Chain Monte Carlo) sampling
method in Bayesian inversion needs many iterations and the calculation process needs
a lot of time, we developed an efficient raytracing algorithm for isotropic and VTI
media. It combined the simple principle of the shooting method and the strong
applicability of the shortest-path method. The algorithm was simple and efficient, and
the high precision travel times and ray paths can be deduced from sparse nodes. It
was beneficial to efficiently obtain the optimized velocity model, which facilitates
real-time microseismic monitoring.
The velocity optimized method proposed in this paper overcomes the problems
of the traditional method, such as less constraint information, poor applicability of
velocity model, large event location error, and low inversion efficiency. It is suitable
for microseismic monitoring under complex geological conditions . The location error
is reduced to ten meters, and the inversion efficiency is improved by tens of times . It
is suitable for field hydraulic fracturing production and provides a strong guarantee
for improving unconventional energy oil and gas recovery.

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