Interaction between Cationic Nano Microsphere and HPAM

This paper intends to deal with one novel profile control agent formed by combination of HPAM and cationic microspheres with different cationic density (CD) by the method of micro-emulsion polymerization. Profile control is of great importance in well stimulation for current oilfield with high water cut. The main profile control agents now are polymer or polymer microspheres. Each of these agents has its own performance advantages. The novel profile control agent is equipped with the advantages of both the agents mentioned above. Analyzed by transmission scan electron microscope (TSEM) and laser particle sizer, the particle size of the original synthesized microsphere and the swelled microsphere in water are 50-100nm and 1-3μm respectively. Analyzed by micro-electrophoresis, the surface potential arrives at its highest value at 30% of the cationic density; aggregation happens when CD is low and the electrostatic force is insufficient to keep the system stable. Due to electrostatic interaction, the synthesized system flocculates at a concentration of 0.02% separately. Measured at varied shear rates, the viscosity of the system can be significantly enhanced by electrostatic interaction. However, this enhancement is not obvious when the salinity is higher than 3%, which indicates that the increasing of viscosity is closely related to the salinity of solution. Moreover, by increasing hydrolysis degree of HPAM, the viscosity of the system can be improved by 20% additionally. Through core displacement test, the synthesized system is proved to have relatively good profile control performance.

AN ADDITIVE POISSON DATA MODELING OF ATTENUATION MAP RECONSTRUCTION FROM POST-INJECTION POSITRON EMISSION TOMOGRAPHY TRANSMISSION SCAN

We present an additive Poisson data modeling of attenuation map reconstruction from post-injection positron emission tomography transmission scan. The transmission scan data are modeled as a collection of independent Poisson observations which consist of true transmission, cross-contamination emission and random coincidences. The mean values of cross-contamination emission and random data are estimated by using Luk's approximation and Zaers' method, respectively. The unknown attenuation map is also modeled using a Gibbs image prior. Under the paradigm of Bayesian statistics, a pre-conditioned conjugate gradient algorithm is then used to compute a maximum a posteriori estimate of the attenuation map by maximizing over the posterior density. Evaluations are conducted on clinical data collected from a CTI EXACT HR+ scanner. Experimental results have indicated that the reconstructed results of attenuation map by the proposed reconstruction algorithm match well with theoretical values of soft tissue, bone and lung under 511 keV photons.