Dissolved organic carbon (DOC) and volatile fatty acids (VFAs) play key roles in the carbon cycling of marine sediment. Both microbially or thermally activated cracking of organic matter often produces high quantities of DOC and VFAs. To uncover the distribution pattern of DOC and VFAs in sediments under both impacts, a submarine mud volcano (SMV), was chosen to denote a model system that could witness how microbial activities react under the mixing of seawater and deeply-sourced fluids in a subsurface environment. We examined the concentration profiles of DOC and several VFAs (lactate, formate, acetate, propionate, and butyrate) in pore water, covering both sulfate reduction and methanogenesis zones, and further numerically modeled six porewater species (DOC, bromide, calcium, magnesium, ammonium, and total alkalinity) to quantify their fluxes from depth as well as the rates of in-situ microbial processes. Apparently, bulk DOC concentrations fluctuated with depths, probably primarily controlled by in situ microbial processes. Lactate was detectable in some samples, while propionate and butyrate were under detection limit. Acetate and formate concentrations were consistently and uniformly low throughout all biogeochemical zones, with a slightly increasing trend with depth at the center of the SMV, suggesting active utilization and turnover by the terminal steps of organic matter mineralization. The numerical modeling suggests that most DOC patterns were primarily influenced by in-situ organic matter degradation, while the impact of upward migrating fluid become more significant at center sites. The calculation of the Gibbs energy of metabolic redox reactions reveals that acetoclastic sulfate reduction yields the highest energy throughout sediment columns and may co-exist with methanogenesis below sulfate reduction zone. In contrast, acetoclastic methanogenesis yields higher energy within sulfate reduction zone than below that region, suggesting it is thermodynamically feasible to co-occur with sulfate reduction in dynamic SMV environments.