本文介绍了根据井间地震数据重建井间速度分布的一种混合波动方程旅行时和波形反演方法。这种方法被称为WTW,它保留着全波反演和旅行时反演的优点;这就是说,这种方法的特点在于合理地快速收敛,这种收敛多少有点不受初始模型的限制,而且,该方法可以分辨出速度模型的详细特征。一般,WTW方法不需要进行旅行时拾取,它的计算费用与全波反演的大致相同。 我们把这种WTW方法应用于由Exxon公司在得克萨斯州Friendswood试验基地采集到的合成数据和野外井间数据中。结果表明,这种WTW层析图象的构造信息比旅行时层析图象的要丰富得多。分辨这种WTW Friendswood层析图象中的隐蔽构造特征所能达到的空间分辨率大约为1.5米,而在旅行时层析图象中,这些隐蔽构造特征仍然是模糊不清或完全就没有被反映出来。这表示中频方式获得的高质量井间数据(清晰的反射)可能要比高频方式获得的中等质量数据(高质量的初至,但反射却埋没于噪声之中)好些。 与用震源井的一条测井曲线重建的速度分布图作比较就可看出,在0米～200米的层段内吻合得相当好。而在200米～300米的层段内,速度变化也吻合得令人满意,但层析图象的速度分布图却与声波测井的速度之间相差了一个DC位移。以上着重强调了这种WTW方法的希望之处和面临的困难;它可以重建模 This paper presents a hybrid wave equation for travel time and waveform inversion based on crosswell seismic data to reconstruct crosswell velocity distribution. This method, known as WTW, preserves the advantages of full-wave inversion and travel-time inversion; that is to say, this method is characterized by reasonably fast convergence, which is somewhat less constrained by the initial model, Moreover, this method can distinguish the detailed characteristics of the velocity model. In general, the WTW method does not need to pick up while traveling, and it is roughly the same computational cost as full-wave inversion. We applied this WTW method to composite data and field crosswell data collected by Exxon’s Friendswood test facility in Texas. The results show that this kind of WTW tomographic image is much more plentiful than the tomographic image when traveling. The spatial resolution that can be achieved by resolving the covert tectonic features in this WTW Friendswood tomographic image is approximately 1.5 m, whereas in the case of tomographic images of travel these covert structural features are still vague or completely uncoated Reflected. This means that high-quality interwell data (clear reflections) obtained by the IF method may be better than medium-quality data (high quality first arrivals, but the reflections are buried in the noise) obtained by the high-frequency method. Compared with the velocity profile reconstructed from a well log of the source well, it can be seen that the anastomosis is quite good within the interval of 0 to 200 meters. However, within 200 m to 300 m, the velocity variations agree well with each other, but the velocity profile of the tomographic images is different from the acoustic logging by a DC displacement. The above highlights the hopes and difficulties faced by this WTW approach; it can be rebuilt