Petrophysical and geophysical constrained inversion of gravity data based on starting and referenced models

To reduce the inherent ambiguity of gravity data modeling in the mineral resources exploration, it is important to incorporate available a priori information into the inversion process. In this paper, we study the use of starting and reference density models, based on two kinds of a priori information: a) by interpolating the physical property available from petrophysical or direct (well logs) knowledge; b) converting in densities another geophysical property, such as resistivity or seismic velocity, previously estimated from geophysical modeling. We use both the kinds of models as either a starting or reference model to optimally solve the regularized inverse problem using the preconditioned conjugate gradient method. We validate both the procedures using synthetic datasets produced by a high-density ore-layer model with drill-hole logs constraints, and then apply them to the field data of an iron ore-deposit and a polymetallic ore region, in southern China. Both the procedures produce an improved and detailed density model; the use of a priori information as a reference model is however preferred, giving indeed a more compact and detailed solution, which seems more suitable to mining exploration.