利用密度迭代法计算气井的井底流压

依据井筒压力与气体密度和湿度之间的函数关系,采用密度迭代法,以井口套压为起点自上而下迭代至井底,计算出井底流压。选择有实际关井测压数据的8口井,将不考虑天然气湿度条件下(干气)用密度迭代法计算的井底流压与实际测压值对比,平均相对误差仅为4.89%;考虑湿度对井底流压的影响,计算了不同气体湿度下的井底流压,与实际测压值之间最大误差为1.369 1%。将用密度迭代法、经验公式及RTA法计算的井底流压与实际测压值进行比较,发现前者的误差最小,而且使用该方法能在不影响气井正常生产的情况下精确计算气井的井底流压,适用于气井整个生产历程中的井底流压计算。

应用包裹体技术恢复气藏古压力

包裹体捕获时的温度和压力反映了油气藏形成时的古温度和古压力,是油气成藏过程研究的一个重要依据。富（CH4）气盐水包裹体是气藏中最主要的一种包裹体类型,对这类包裹体捕获温度和压力的恢复最大的技术难点是其中气体（CH4）含量的精确测定。通过建立CH4气体拉曼位移值与包裹体内压的相关曲线,根据包裹体总体积和成分保持恒定的原则构建迭代计算模型,可快速准确计算出含CH4盐水包裹体的捕获压力。该方法应用于川南隆32井中奥陶统宝塔组微晶灰岩中的包裹体古压力研究,计算结果显示包裹体的捕获压力为884.08～1 249.32 bar,压力系数约为1.3～1.8,证明了包裹体捕获时地层流体为超压状态。

Study on Interaction Between Two Parallel Plates with Iteration Method in Functional Theory

By introducing the functional theory into the calculation of electric double layer （EDL） interaction, the interaction energies of two parallel plates were calculated respectively at low, moderate, and high potentials. Compared with the results of two existing methods, Debye-Hückel and Langmuir methods, which are applicable just to the critical potentials and perform poorly in the intermediate potential, the functional approach not only has much simpler expression of the EDL interaction energy, but also performs well in the entire range of potentials.

A modified method to calculate reliability index using maximum entropy principle

Routine reliability index method, first order second moment (FOSM), may not ensure convergence of iteration when the performance function is strongly nonlinear. A modified method was proposed to calculate reliability index based on maximum entropy (MaxEnt) principle. To achieve this goal, the complicated iteration of first order second moment (FOSM) method was replaced by the calculation of entropy density function. Local convergence of Newton iteration method utilized to calculate entropy density function was proved, which ensured the convergence of iteration when calculating reliability index. To promote calculation efficiency, Newton down-hill algorithm was incorporated into calculating entropy density function and Monte Carlo simulations (MCS) were performed to assess the efficiency of the presented method. Two numerical examples were presented to verify the validation of the presented method. Moreover, the execution and advantages of the presented method were explained. From Example 1, after seven times iteration, the proposed method is capable of calculating the reliability index when the performance function is strongly nonlinear and at the same time the proposed method can preserve the calculation accuracy; From Example 2, the reliability indices calculated using the proposed method, FOSM and MCS are 3.823 9, 3.813 0 and 3.827 6, respectively, and the according iteration times are 5, 36 and 10 6 , which shows that the presented method can improve calculation accuracy without increasing computational cost for the performance function of which the reliability index can be calculated using first order second moment (FOSM) method.

KSSOLV-GPU:an Efficient GPU-Enabled MATLAB Toolbox for Solving the Kohn-Sham Equations within Density Functional Theory in Plane-Wave Basis Set

KSSOLV(Kohn-Sham Solver)is a MATLAB(Matrix Laboratory)toolbox for solving the Kohn-Sham density functional theory(KS-DFT)with the plane-wave basis set.In the KS-DFT calculations,the most expensive part is commonly the diagonalization of Kohn-Sham Hamiltonian in the self-consistent field(SCF)scheme.To enable a personal computer to perform medium-sized KS-DFT calculations that contain hundreds of atoms,we present a hybrid CPU-GPU implementation to accelerate the iterative diagonalization algorithms implemented in KSSOLV by using the MATLAB built-in Parallel Computing Toolbox.We compare the performance of KSSOLV-GPU on three types of GPU,including RTX3090,V100,and A100,with conventional CPU implementation of KSSOLV respectively and numerical results demonstrate that hybrid CPU-GPU implementation can achieve a speedup of about 10 times compared with sequential CPU calculations for bulk silicon systems containing up to 128 atoms.

An Independent Component Analysis Algorithm through Solving Gradient Equation Combined with Kernel Density Estimation

A new algorithm for linear instantaneous independent component analysis is proposed based on maximizing the log-likelihood contrast function which can be changed into a gradient equation.An iterative method is introduced to solve this equation efficiently.The unknown probability density functions as well as their first and second derivatives in the gradient equation are estimated by kernel density method.Computer simulations on artificially generated signals and gray scale natural scene images confirm the efficiency and accuracy of the proposed algorithm.