The objective of the present paper is to provide geochemical and palynological data to characterize lignites and carbonaceous shales from Panandhro, northwestern Kutch Basin, Gujarat, Western India, in terms of their hydrocarbon potential, thermal maturity, sequence stratigraphic settings and depositional palaeoenvironment. The samples, collected in Panandhro lignite mine, belong to Naredi Formation of Late Paleocene-Early Eocene age. The geochemical results are based on proximate analysis, ultimate analysis, X-ray diffraction and Rock-Eval py-rolysis analyses, whereas palynological data include palynofossil composition and thermal alteration index (TAI). The TOC, hydrogen index (HI), cracked hydrocarbon (S2), bitumen index (BI), quality index (QI), and the total genetic potential (S1+S2) values indicate that the studied lignites and carbonaceous shales have good source rock potential. The organic matter is predominantly of type II and type II/III kerogen, which has potential to generate oil as well as gas. Thermal maturity determined from thermal alteration index (TAI), Tmax and production index (PI) indicates that the organic matter is immature, and in the diagenesis stage of organic matter transformation. The deposition of the studied carbonaceous shales and lignites took place in palaeoenvironments varying from brackish mangrove to freshwater swamp. This study indicates that the proportion of ferns, palms, volatile matter content, S/C, H/C ratios, as well as the presence of siderite and quartz can be used as an indicator of accommodation trends in the coal depositional system. The Panandhro carbonaceous shales and lignites were deposited during the lowstand systems tract with many cycles of small magnitude trangressive-regressive phases. Thus, the geochemistry and ecological palynology are useful not only for the investigation of coal quality and origin, but also to infer accommodation space settings of the mire. This can be gainfully utilized in the coal industry for coal mine planning, development and exploitation, because of the predictive ability to infer changes in stratigraphy and coal quality.