Low-frequency laboratory measurements of the elastic properties of solids using a distributed acoustic sensing system

In recent decades,low-frequency(LF)experiments based on the forced-oscillation(FO)method have become common practice in many rock physics laboratories for measuring the elastic and anelastic properties of rocks.However,the use of the electronic displacement sensors in traditional acquisition systems of FO devices such as conventional capacitive transducers or strain gauges seriously limits both the efficiency and productivity of LF measurements,and,due to the limited contact area of the displacement sensors with a sample under test,increases the requirements for sample homogeneity.In this paper,we present the first results obtained in the development of a new laboratory method elaborated to measure the elastic properties of solids.The method is a further development of the FO method where traditional data acquisition is replaced by acquisition based on fiber-optic distributed acoustic sensing(DAS)technology.The new method was tested in a laboratory study using two FO setups designed for measurements under uniaxial and confining pressures.The study was carried out on a sample made from polymethyl methacrylate(PMMA)and an aluminium standard,first under uniaxial pressure at FO frequencies of 1,10,30,60 and 100 Hz,and then under confining pressure at an FO frequency of 1 Hz.Both uniaxial and confining pressures were equal to 10 MPa,and the strain in the PMMA sample in all measurements did not exceed 4×10^(-8).The performance of DAS acquisition was compared with the measurements conducted at a strain of 1×10^(-6) using the traditional FO method based on the use of semiconductor strain gauges and the ultrasonic method.The results of the DAS measurements are in good agreement with the FO measurements carried out using semiconductor strain gauges and with the literature data.

Reservoir and lithofacies shale classification based on NMR logging

Shale gas reservoirs have fine-grained textures and high organic contents,leading to complex pore structures.Therefore,accurate well-log derived pore size distributions are difficult to acquire for this unconventional reservoir type,despite their importance.However,nuclear magnetic resonance(NMR)logging can in principle provide such information via hydrogen relaxation time measurements.Thus,in this paper,NMR response curves(of shale samples)were rigorously mathematically analyzed(with an Expectation Maximization algorithm)and categorized based on the NMR data and their geology,respectively.Thus the number of the NMR peaks,their relaxation times and amplitudes were analyzed to characterize pore size distributions and lithofacies.Seven pore size distribution classes were distinguished;these were verified independently with Pulsed-Neutron Spectrometry(PNS)well-log data.This study thus improves the interpretation of well log data in terms of pore structure and mineralogy of shale reservoirs,and consequently aids in the optimization of shale gas extraction from the subsurface.