This paper introduces a complete methodology for abdominal sounds analysis, from signal acquisition to statistical data analysis. The goal is to evaluate if and how phonoenterograms can be used to detect different functioning modes of the normal gastrointestinal tract, both in terms of localization and of time evolution during the digestion. After the description of the acquisition protocol and the employed instrumentation, several signal processing steps are presented: wavelet denoising and segmentation, artifact suppression and source localization. Next, several physiological features are extracted from the processed signals issued from a data-base of 14 healthy volunteers, recorded during 3 hours after a standardized meal. Data analysis is performed using a multi-factorial statistical method. Based on the introduced approach, we show that the abdominal regions of healthy volunteers present statistically significant phonoenterographic characteristics, which evolve differently during the normal digestion. The most significant feature allowing to distinguish regions and time differences is the number of recorded sounds, but important information is also carried by sound amplitudes, frequencies and durations. Depending on the considered feature, the sounds produced by different abdominal regions (especially stomach, ileo-caecal and lower abdomen regions) present a specific distribution over space and time. This information, statistically validated, is usable in further studies as a comparison term with other normal or pathological conditions.