Reservoir reconstruction technologies for coalbed methane recovery in deep and multiple seams

Multiple coal seams widely develop in the deep Chinese coal-bearing strata. Ground in situ stress and coal seam gas pressure increase continuously with the increase of the mining depth, and coal and gas outburst disasters become increasingly severe. When the coal is very deep, the gas content and pressure will elevate and thus coal seams tends to outburst-prone seams. The safety and economics of exploited firstmined coal seams are tremendously restricted. Meanwhile, the multiple seams occurrence conditions resulted in different methane pressure systems in the coal-bearing strata, which made the reservoir reconstruction of coal difficult. Given the characteristics of low saturation, low permeability, strong anisotropy and soft coal of Chinese coal seams, a single hydraulic fracturing surface well for reservoir reconstruction to pre-drain the coalbed methane(CBM) of multiple seams concurrently under the different gas pressure systems has not yet gained any breakthroughs. Based on analyses of the main features of deep CBM reservoirs in China, current gas control methods and the existing challenges in deep and multiple seams, we proposed a new technology for deep CBM reservoir reconstruction to realize simultaneous high-efficiency coal mining and gas extraction. In particular, we determined the first-mined seam according to the principles of effectiveness and economics, and used hydraulic fracturing surface well to reconstruct the first-mined seam which enlarges the selection range of the first-mined seam. During the process of mining first-mined seam, adjacent coal seams could be reconstructed under the mining effect which promoted high-efficiency pressure relief gas extraction by using spatial and comprehensive gas drainage methods(combination of underground and ground CBM extraction methods). A typical integrated reservoir reconstruction technology, ‘‘One well for triple use", was detailed introduced and successfully applied in the Luling coal mine. The application showed that the proposed technology could effectively promote coal mining safety and simultaneously high-efficiency gas extraction.

Imaging algorithm of multi-ship motion target based on compressed sensing

An imaging algorithm based on compressed sensing（CS） for the multi-ship motion target is presented. In order to reduce the quantity of data transmission in searching the ships on a large sea area, both range and azimuth of the moving ship targets are converted into sparse representation under certain signal basis. The signal reconstruction algorithm based on CS at a distant calculation station, and the Keystone and fractional Fourier transform（FRFT） algorithm are used to compensate range migration and obtain Doppler frequency. When the sea ships satisfy the sparsity, the algorithm can obtain higher resolution in both range and azimuth than the conventional imaging algorithm. Some simulations are performed to verify the reliability and stability.

Joint DOA and polarization estimation for unequal power sources based on reconstructed noise subspace

In most literature about joint direction of arrival（DOA） and polarization estimation, the case that sources possess different power levels is seldom discussed. However, this case exists widely in practical applications, especially in passive radar systems. In this paper, we propose a joint DOA and polarization estimation method for unequal power sources based on the reconstructed noise subspace. The invariance property of noise subspace（IPNS） to power of sources has been proved an effective method to estimate DOA of unequal power sources. We develop the IPNS method for joint DOA and polarization estimation based on a dual polarized array. Moreover, we propose an improved IPNS method based on the reconstructed noise subspace, which has higher resolution probability than the IPNS method. It is theoretically proved that the IPNS to power of sources is still valid when the eigenvalues of the noise subspace are changed artificially. Simulation results show that the resolution probability of the proposed method is enhanced compared with the methods based on the IPNS and the polarimetric multiple signal classification（MUSIC） method. Meanwhile, the proposed method has approximately the same estimation accuracy as the IPNS method for the weak source.

3D image reconstruction with controllable spatial filtering based on correlation of multiple periodic functions in computational integral imaging

We propose a novel method of slice image reconstruction with controllable spatial filtering by using the correlation of periodic delta-function arrays （PDFAs） with elemental images in computational integral imaging. The multiple PDFAs, whose spatial periods correspond to object＇s depths with the elemental image array （EIA）, can generate a set of spatially filtered EIAs for multiple object depths compared with the conventional method for the depth of a single object. We analyze a controllable spatial filtering effect by the proposed method. To show the feasibility of the proposed method, we carry out preliminary experiments for multiple objects and present the results.

Dual-basis reconstruction techniques for tomographic PIV

As an inverse problem, particle reconstruction in tomographic particle image velocimetry attempts to solve a large-scale underdetermined linear system using an optimization technique. The most popular approach, the multiplicative algebraic reconstruction technique(MART), uses entropy as an objective function in the optimization. All available MART-based methods are focused on improving the efficiency and accuracy of particle reconstruction. However, those methods do not perform very well on dealing with ghost particles in highly seeded measurements. In this report, a new technique called dual-basis pursuit(DBP), which is based on the basis pursuit technique, is proposed for tomographic particle reconstruction. A template basis is introduced as a priori knowledge of a particle intensity distribution combined with a correcting basis to enable a full span of the solution space of the underdetermined linear system. A numerical assessment test with 2D synthetic images indicated that the DBP technique is superior to MART method, can completely recover a particle field when the number of particles per pixel(ppp) is less than 0.15, and can maintain a quality factor Q of above 0.8 for ppp up to 0.30. Unfortunately, the DBP method is difficult to utilize in 3D applications due to the cost of its excessive memory usage. Therefore, a dual-basis MART was designed that performed better than the traditional MART and can potentially be utilized for 3D applications.