Method for simultaneous inversion of five reservoir parameters of submarine gas reservoirs using P-WAVE velocity and density data

A device for simultaneous inversion of five reservoir parameters of submarine gas reservoirs using P-wave velocity and density data, comprising:

• data acquiring and rock physics modeling module, acquiring, via a logging equipment, an observed P-wave velocity
• (
• V
• p
• obs
• )
• ,
• an observed density
• (
• ρ
• b
• obs
• )
• ,
• and a reservoir distribution range, and measuring an actual value of a free gas saturation, a porosity, and mineral composition ratios of a rock skeleton to validate inversion accuracy;
• constructing a physically-based P-wave velocity model and a bulk density model of the a reservoir rock using a simplified two-phase Biot equation that incorporates a depth-dependent consolidation factor (α) which is depth-dependent, a weighted average equation of mixed fluid that uses a calibration factor (χ) to model patchy saturation, and a volume density equation, wherein these models incorporate physical properties of clay, quartz, carbonate, sea water, and natural gas;
• geological experience obtaining and optimization problem constructing module, obtaining experienced range values of a free gas saturation, a range of the porosity, and a range of each of the mineral composition ratios;
• setting the free gas saturation (Sg), the porosity (φ), a clay content (Vclay), a carbonate content (Vcar), and a water-gas mixture calibration factor (χ) as five unknown variables to be inverted in the P-wave velocity model and the bulk density model;
• associating the P-wave velocity model with the observed P-wave velocity and the bulk density model with the observed density;
• and
• constructing a multi-dimensional nonlinear constrained optimization problem with a goal of minimizing a sum of mean squared errors between model-calculated values and observed values, while setting physically-based variable ranges for each inverted unknown variable;
• wherein, 0≤Sg≤0.5, 0≤Vclay≤1,
• 0≤Vcar≤1, 0≤Vclay+Vcar≤1, 0≤χ≤1;
• optimization solution and parameter outputting module, after constructing the optimization problem, simultaneously obtaining values of the five reservoir parameters from logging data and initial iteration values by using multiple sets of initial iteration values randomly selected within the variable ranges and solving the optimization problem with an interior-point algorithm, while dynamically adjusting the consolidation factor for each of the reservoir distribution points during iteration;
• and judging inversion accuracy by calculating a root mean square error between inversion results and the observed reservoir parameters, until convergence;
• and
• outputting inversion values for validating inversion accuracy together with a corresponding consolidation factor for predicting a two dimensional (2D) reservoir parameter prediction or a three dimensional (3D) reservoir parameter;
• seismic data inversion and reservoir parameters distribution inversion outputting module, during a prediction process, acquiring submarine gas reservoir seismic data collected by a seismic equipment, inverting the submarine gas reservoir seismic data, using a post-stack inversion method for post-stack seismic data or an amplitude variation with offset (AVO) inversion method for pre-stack seismic data, to obtain a 2D P-wave velocity profile or a 3D P-wave velocity profile and a 2D density profile or a 3D density profile;
• using the corresponding consolidation factor, the 2D P-wave velocity profile or 3D P-wave velocity profile, the 2D density profile or the 3D density profile as inputs to the optimization problem constructed with the P-wave velocity model and the bulk density model, repeating an inversion process of each seismic common depth point (CDP) trace and each depth point to obtain the inverted unknown variables of the five reservoir parameters;
• outputting a spatially indexed 2D reservoir parameter distribution profile or a spatially indexed 3D reservoir parameter distribution profile of the submarine gas reservoir, thereby enabling improved reservoir volume evaluation and development optimization through spatially-distributed physical parameters of the gas reservoir.