Transmissive 2-bit anisotropic coding metasurface

Coding metasurfaces have attracted tremendous interests due to unique capabilities of manipulating electromagnetic wave. However, archiving transmissive coding metasurface is still challenging. Here we propose a transmissive anisotropic coding metasurface that enables the independent control of two orthogonal polarizations. The polarization beam splitter and the OAM generator have been studied as typical applications of anisotropic 2-bit coding metasurface. The simulated far field patterns illustrate that the x and y polarized electromagnetic waves are deflected into two different directions, respectively. The anisotropic coding metasurface has been experimentally verified to realize an orbital angular momentum (OAM) beam with l = 2 of right-handed polarized wave, resulting from both contributions from linear-to-circular polarization conversion and the phase profile modulation. This work is beneficial to enrich the polarization manipulation field and develop transmissive coding metasurfaces.

An efficient Bayesian neural network surrogate algorithm for shape detection

We present an efficient Bayesian algorithm for identifying the shape of an object from noisy far field data. The data is obtained by illuminating the object with one or more incident waves. Bayes' theorem provides a framework to find a posterior distribution of the parameters that determine the shape of the scatterer. We compute the distribution using the Markov Chain Monte Carlo (MCMC) method with a Gibbs sampler. The principal novelty of this work is to replace the forward far-field-ansatz wave model (in an unbounded region) in the MCMC sampling with a neural-network-based surrogate that is hundreds of times faster to evaluate. We demonstrate the accuracy and efficiency of our algorithm by constructing the distributions, medians and confidence intervals of non-convex shapes using a Gaussian random circle prior. References Y. Chen. Inverse scattering via Heisenberg’s uncertainty principle. Inv. Prob. 13 (1997), pp. 253–282. doi: 10.1088/0266-5611/13/2/005 D. Colton and R. Kress. Inverse acoustic and electromagnetic scattering theory. 4th Edition. Vol. 93. Applied Mathematical Sciences. References C112 Springer, 2019. doi: 10.1007/978-3-030-30351-8 R. DeVore, B. Hanin, and G. Petrova. Neural Network Approximation. Acta Num. 30 (2021), pp. 327–444. doi: 10.1017/S0962492921000052 M. Ganesh and S. C. Hawkins. A reduced-order-model Bayesian obstacle detection algorithm. 2018 MATRIX Annals. Ed. by J. de Gier et al. Springer, 2020, pp. 17–27. doi: 10.1007/978-3-030-38230-8_2 M. Ganesh and S. C. Hawkins. Algorithm 975: TMATROM—A T-matrix reduced order model software. ACM Trans. Math. Softw. 44.9 (2017), pp. 1–18. doi: 10.1145/3054945 M. Ganesh and S. C. Hawkins. Scattering by stochastic boundaries: hybrid low- and high-order quantification algorithms. ANZIAM J. 56 (2016), pp. C312–C338. doi: 10.21914/anziamj.v56i0.9313 M. Ganesh, S. C. Hawkins, and D. Volkov. An efficient algorithm for a class of stochastic forward and inverse Maxwell models in R3. J. Comput. Phys. 398 (2019), p. 108881. doi: 10.1016/j.jcp.2019.108881 L. Lamberg, K. Muinonen, J. Ylönen, and K. Lumme. Spectral estimation of Gaussian random circles and spheres. J. Comput. Appl. Math. 136 (2001), pp. 109–121. doi: 10.1016/S0377-0427(00)00578-1 T. Nousiainen and G. M. McFarquhar. Light scattering by quasi-spherical ice crystals. J. Atmos. Sci. 61 (2004), pp. 2229–2248. doi: 10.1175/1520-0469(2004)061<2229:LSBQIC>2.0.CO;2 A. Palafox, M. A. Capistrán, and J. A. Christen. Point cloud-based scatterer approximation and affine invariant sampling in the inverse scattering problem. Math. Meth. Appl. Sci. 40 (2017), pp. 3393–3403. doi: 10.1002/mma.4056 M. Raissi, P. Perdikaris, and G. E. Karniadakis. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys. 378 (2019), pp. 686–707. doi: 10.1016/j.jcp.2018.10.045 A. C. Stuart. Inverse problems: A Bayesian perspective. Acta Numer. 19 (2010), pp. 451–559. doi: 10.1017/S0962492910000061 B. Veihelmann, T. Nousiainen, M. Kahnert, and W. J. van der Zande. Light scattering by small feldspar particles simulated using the Gaussian random sphere geometry. J. Quant. Spectro. Rad. Trans. 100 (2006), pp. 393–405. doi: 10.1016/j.jqsrt.2005.11.053

Multiple In-Situ Stress Measurements in Carbonate Reservoirs for CO2 Injection Capability Assessment and Far-Field Strain Calibrations

The scope of this work is to measure downhole fracture-initiation pressures in multiple carbonate reservoirs located onshore about 50 km from Abu Dhabi city. The objective of characterizing formation breakdown across several reservoirs is to quantify the maximum gas and CO2 injection capacity on each reservoir layer for pressure maintenance and enhance oil recovery operations. This study also acquires pore pressure and fracture closure pressure measurements for calibrating the geomechanical in-situ stress model and far-field lateral strain boundary conditions. Several single-probe pressure drawdown and straddle packer microfrac injection tests provide accurate downhole measurements of reservoir pore pressure, fracture initiation, reopening and fracture closure pressures. These tests are achieved using a wireline or pipe-conveyed straddle packer logging tool capable to isolate 3 feet of openhole formation in a vertical pilot hole across five Lower Cretaceous carbonate reservoirs zones. The fracture closure pressures are obtained from three decline methods during the pressure fall-off after fracture propagation injection cycle. The three methods are: (1) square-root of the shut-in time, (2) G-Function pressure derivative, and (3) Log-Log pressure derivative. The far-field strain values are estimated by multi-variable regression from the microfrac test data and the core-calibrated static elastic properties of the formations where the stress tests are done. The reservoir pressure across these carbonate formations are between 0.48 to 0.5 psi/ft with a value repeatability of 0.05 psi among build-up tests and 0.05 psi/min of pressure stability. The formation breakdown pressures are obtained between 0.97 and 1.12 psi/ft over 5,500 psi above hydrostatic pressure. The in-situ fracture closure measurements provide the magnitude of the minimum horizontal stress 0.74 - 0.83 psi/ft which is used to back-calculate the lateral strain values (0.15 and 0.72 mStrain) as far-field boundary condition for subsequent geomechanical modeling. These measurements provide critical subsurface information to accurately predict wellbore stability, hydraulic fracture containment and CO2 injection capacity for effective enhance oil recovery within these reservoirs. This in-situ stress wellbore data represents the first of its kind in the field allowing petroleum and reservoir engineers to optimize the subsurface injection plans for efficient field developing.

Application of Integrated Far-Field Diversion Technology in Multistage Acid-Fracturing: Lesson Learnings from Unconventional Field North Kuwait

The unconventional Bahrah field is a high potential field which poses several challenges in terms of hydrocarbon flow assurance through highly heterogeneous tight carbonate intervals with poor reservoir quality and curtailed mobility. Due to this, the field development strategies have prioritized well completion using horizontal acid fracturing technology over vertical wells. During fracturing, the acid system tends to form highly conductive channels in the formation. Most of the fluid will flow into the path of least resistance leaving large portions of the formation untreated. As a result, the fracturing treatment options dwindle significantly, thus reservoir stimulation results are not optimum in each stage. Achieving complete wellbore coverage is a challenge for any acid frac treatment performed in long lateral with variations in reservoir characteristics. The multistage acid fracturing using Integrated Far-field Diversion (IFD) is performed using selective openhole completion, enabling mechanical annular segmentation of the wellbore using swellable packers and sliding sleeves. The mechanical as well as chemical diversion in IFD methodology is highly important to the overall stimulation success. The technique includes pumping multiple self-degrading particle sizes, considering the openhole annular space and wide presence of natural fractures, followed by in-situ HCL based crosslinked system employed for improving individual stage targets. A biomodal strategy is employed wherein larger particles are supplemented with smaller that can bridge pore throats of the larger particles and have the desired property of rigidity and develop a level of suppleness once exposed to reservoir conditions. The IFD diversion shifts the fracture to unstimulated areas to create complex fractures that increase reservoir contact volume and improving overall conductivity. This paper examines IFD in acid fracturing and describes the crucial diversion strategy. Unlike available diverters used in other fields, the particulates are unaffected at low pH values and in live acids. Proper agent selection and combination with in-situ crosslink acid effectively plug the fracture generated previously and generate pressure high enough to initiate another fracture for further ramification. The optimization and designing of the IFD diversion in each stage plays a key role and has helped to effectively plug fractures and realize segmentation. Concentration of diversion agents, volume of fluid system and open-hole stage length sensitivity plays vital role for the success of this treatment. The application of IFD methodology is tuned as fit-for-purpose to address the unique challenges of well operations, formation technical difficulties, high-stakes economics, and untapped high potential from this unconventional reservoir. A direct result of this acid fracturing treatment is that the post-operation data showed high contribution of all fractured zones along the section in sustained manner. Furthermore, this methodology can be considered as best practice for application in unconventional challenges in other fields.

Analog and Photon Signal Splicing for CO2-DIAL Based on Piecewise Nonlinear Algorithm

In the CO2 differential absorption lidar (DIAL) system, signals are simultaneously collected through analog detection (AD) and photon counting (PC). These two kinds of signals have their own characteristics. Therefore, a combination of AD and PC signals is of great importance to improve the detection capability (detection range and accuracy) of CO2-DIAL. The traditional signal splicing algorithm cannot meet the accuracy requirements of CO2 inversion due to unreasonable data fitting. In this paper, a piecewise least square splicing algorithm is developed to make signal splicing more flexible and efficient. First, the lidar signal is segmented, and according to the characteristics of each signal, the best fitting parameters are obtained by using the least square fitting with different steps. Then, all the segmented and fitted signals are integrated to realize the effective splicing of the near-field AD signal and the far-field PC signal. A weight gradient strategy is also adopted in signal splicing, and the weights of the AD and PC signals in the spliced signal change with the height. The splicing effect of the improved algorithm is evaluated by the measured signal, which are obtained in Wuhan, China, and the splice of the AD and PC signals in the range of 800–1500 m are completed. Compared with the traditional method, the evaluation parameter R2 and the residual sum of squares of the spliced signal are greatly improved. The linear relationship between the AD and PC signals is improved, and the fitting R2 of differential absorption optical depth reaches 0.909, indicating that the improved signal splicing algorithm can well splice the near-field AD signal and the far-field PC signal.