- [Instructor] Okay so now I have, we'll go to the second part of my talk. In the first part, we talk about the core skill. Core skill heterogeneous structures of the shales. Now we will narrow down to focus on the kerogens and want to know the heterogeneous structures of the kerogens. Again this is pattern of shales, and we can see that kerogens, this is a field SEM result for kerogens, and you can see this structure has, indeed shows some heterogeneities. And we want to quantify this. And current way to quantify this heterogeneity of the samples, is mostly by electron microscopy. And usually if you want to see the structure deep inside the sample, you and to slice the sample and it's very destructive way for the samples. And also using a fan, it can gather fine structures, but it's very time consuming. If you use gas absorption method, then it will be more model independent. Most of the scattering method, also most applied to the homogenous structure. There is a strong need for us to think of new way to characterize heterogeneous structure of the materials, which is non-destructive model independent and efficient and can be applied to homogeneous samples. This push us to think out new way, and again because kerogen has a lot of nanostructure, so it's very simple for using small angle neutron scattering. Let me briefly introduce technique that we put box samples. We don't slice sample. You put the box samples inside the bins. This is coming x-ray or neutron beams and keep the sample, interact with the sample and therefore the beam will be, the radiation will be scattered. And this will detect by the detectors and detector record the different angle intensity at different angles. And this Q is wave vectors that is related to angles. Q is reciprocal to the length scales. So large Q means small length scales and in this, we have SANS and ultra small-angle neutron scattering. And is cover the length scale to one millimeter to 20 micro meters. And this is our typical SANS data look like. You are plotting intensity versus Q. And so this is we use kerogen isolated from the shale rocks with three different maturity. This is vitrinite reflectance and index for these three samples from 0.6 to 1.6. We use the typical way to analyze the data, to use nitrogen absorption, get BET surface area and then pore volume. You can see that especially for pore volume, it's really very similar for these three samples. And so we need, indeed need new way to characterize the samples. So in our newly developed Generalized Porod's Scattering Law Method, GPSLM method, we treat this heterogenous sample as this. That basically you can see the system has different domain with different color. This color represents different scattering length density. And then scattering length density is related to the chemical compositions of the element. So it will give you chemical informations. And so in this F means fluid. So in the background, we can inject different fluid. In my case, I injected some gas. And this changing the fluid as a background, we are keep changing the contrast, the scattering length density of the backgrounds. Because the contrast keep changing, so we sense different interface and we can extract the heterogeneous property of the materials. This is the basic idea. And in this instance, we can simulate, in this instance, three important parameters can characterize these systems. First is average scattering length density, Rho A. So Rho A basically use sum over these interface and sum over the, average over the scattering length density on the interface in these dotted lines. And you do average and you get Rho A. And Rho M square is we average over the scattering length density squares on the surface of each domains and the most important parameter is the heterogeneous parameter. That is basically the mean-square displacement. Mean-square deviations of the scattering length density relative to the average scattering length density of the systems. So this heterogeneity delta H is larger. This means that the system is more heterogeneous. If delta H is smaller, means that system is more homogenous. So these two parameter can characterize these systems and our GPSLM method can catch all these three parameters. So this is our result. So we get the average scattering length density as the function of vitrinite reflectance R zeros and we found that when maturity is larger, the average scattering length density is larger. This means that you have a less hydrogen content, which makes sense, because when kerogen become more mature the large molecule would break down into smaller and then give out hydrogen. So hydrogen content becomes smaller. And our delta H heterogeneity parameter versus maturity, we can see that when kerogen become more mature, the materials become more homogenous. This also makes sense because when things get more mature, then different domain all become more like carbon. So the overall system will become more homogenous. And also this method also give us specific surface area. Means the surface areas per grams of the samples and compare with BET surface area, you can see that they are very similar. This is a very accurate method.