Lacustrine fan deltas, key depositional systems at basin margins, serve as crucial hydrocarbon accumulation sites. Previous studies have largely focused on depositional slope, overlooking the role of source-area slope and its coupling with grain size in source-to-sink steep-slope zones. Understanding this grain-size control on fan-delta architecture is crucial for predicting subsurface reservoir distribution, dimensions, and stacking patterns. Located in the North China Craton, the Luanping Basin features well-exposed Yuying (Y) and Duiwogoumen (D) sections of the Lower Cretaceous Xiguayuan Formation, which offer ideal outcrops for analyzing fan-delta architecture in source-to-sink steep-slope zones. Unmanned aerial vehicle (UAV) digital models reveal that fan-delta architectural elements in source-to-sink steep-slope zones are dominated by lobes, accompanied by rare distributary channels and slump deposits. Steeper source-area slopes promote high-concentration, high-velocity sediment flows, which favor lobe deposition and suppress erosional channel development, thereby controlling the relative dominance of lobes over channels. Under such steep-slope settings, field surveys and flume-tank experiments jointly elucidate how grain size governs lobe architecture and its underlying mechanisms. Fine-grained sediments exhibit higher fluidity and slower settling rates, enabling broader dispersion and the formation of wide, sheet-like lobes with high width-to-thickness ratios and predominantly vertical stacking. In contrast, coarse-grained sediments show lower fluidity, poorer stability, and faster settling, leading to rapid deposition that produces narrow, tongue-shaped lobes with low width-to-thickness ratios, dominated by lateral migration and associated with deeper incised channels. Thus, fan-delta architecture in source-to-sink steep-slope zones is governed by a dual control: source-area slope determines the lobe-dominated pattern, and grain size dictates lobe geometry and stacking. This study provides a mechanistic framework for predicting reservoir distribution in analogous systems.
Sun et al. (Wed,) studied this question.