The complicated source-reservoir-assemblage characteristics of lacustrine tight oil sand in China are the main controlling factors of tight reservoir oiliness (i.e., oil richness). Several studies have focused on qualitative description of source-reservoir-assemblage characteristics without quantitative assessment. In this study, reservoir-source-assemblage (RSA) has been evaluated quantitatively by fitting the RSA log in the evaluation of Qijia Depression in the Songliao Basin. Total organic carbon (TOC) and sand volume (Vs) logs are used to fit the RSA log in three steps: (1) TOC and Vs log fitting and normalization, (2) RSA log fitting, and (3) extraction of root-mean-square (rms) amplitude and frequency (Frq(0)) information from the RSA log. The rms represents the reservoir capability and hydrocarbon potential, and Frq(0) represents the interbedding frequency that changes with the lake level. Positive values (0–1] of the RSA log correspond to a high lake level, whereas negative values [, 0) correspond to a low lake level. Based on RSA log values, we defined the parameter RSAsuf, a product of rms and Frq(0), to quantitatively evaluate the tight oil sweet spot. RSAsurf serves as tight oil sweet spot indicator and correlates positively to oil richness. As a result, four types of effective reservoirs (RI, RII, RIII, and RIV), two types of effective sources (SI and SII), and three types of RSAs (R-S-R, S-R-S, and S-S-R) are identified based on cores and RSA logs. High RSAsuf values on the isoline map indicate the sweet spot zones around the G933 and J392 well areas, which correlates very well with the oilfield test data. The approach is appropriate for lacustrine basins with complicated RSA, in which RSA logs serve as indicator for the sedimentary rhythm, reservoir capability, and hydrocarbon potential.