Natural fractures (NFs), ubiquitous in source rocks (SRs) commonly referred to as shale reservoirs, are posited to influence fluid flow. Quantification of post-stimulation flow and drainage architecture, consisting of hydraulic fractures (HFs) and NFs, have remained challenging. Quite often, NFs are implicitly accounted for, and when explicitly represented with discrete fracture networks (DFNs), the models are inadequately constrained. This study used well production, microseismic (MS) events, core plug permeability, core section images, borehole image (BHI) interpretations, core evaluation, and burial, tectonic and thermal history for the Longmaxi Shale (Sichuan Basin, China). Analytical solutions for transient linear flow, diagnosed from production data, led to linear flow parameters (LFPs) for scenarios with infinite and finite conductivity fractures. System permeability, in nandodarcy (nD) range, was derived using planar HF geometry validated by MS events. NF surface area multipliers (NFSAMs) stochastically accounted for the large surface area arising from reactivation of NFs. Subsequent matrix permeability, for a range of NFSAMs, was in pico- to sub-picodarcy (pD) range. NF rupture area derived from synthetic microseismicity and associated source properties constrained the representative NFSAM. For further validation, matrix permeability was derived using other techniques. One, laboratory-derived core plug permeability was stress-corrected for experimental and in situ conditions. Two, a core section image, with closely spaced sub-vertical and parallel NFs, guided analysis of flush production. Three, burial, tectonic and thermal history data was used in simplified basin and petroleum system modelling (BPSM) to account for petroleum expulsion and persistence of abnormal pore pressure over a geological timescale. Average matrix permeability from multiscale data and multiphysics assessments was scale- and play-independent. Lastly, DFN flow area and a simplistic architecture, comprising systematic NFs, allowed quantification of the average NF density for stimulated reservoir volume (SRV). Comparison of the aforementioned density with that from BHI interpretations and core evaluation offered a qualitative validation.