In this study, we take a fresh look at the cross-correlations between WTI crude oil market and U.S. stock market from the perspective of econophysics. We choose the three major U.S. stock indices (i.e., DJIA, NASDAQ and S&P 500) as the research objects and select the sample data from Jan 2, 2002 to Jun 29, 2012. In the empirical process, first, using a statistical test in analogy to the Ljung-Box test, we find that there are cross-correlations between WTI and DJIA, WTI and NASDAQ, and WTI and S&P 500 at the 5% significance level. Then, employing the multifractal detrended cross-correlation analysis (MF-DCCA) method, we find that the cross-correlated behavior between WTI crude oil market and U.S. stock market is nonlinear and multifractal. An interesting finding is that the cross-correlation exponent is smaller than the average scaling exponent when q<0, and larger than the average scaling exponent when q>0. Finally, using the rolling windows method, which can capture the dynamics of cross-correlations, we find that there are three special periods whose time-varying Hurst exponents are different from the others.