Type-curve analysis methods

Liquid Permeability Determination from Vacuum Imbibition in Tight/Shale Core Plugs

“…For one-dimensional liquid vacuum imbibition into tight and shale core plugs, it is assumed that (1) gravity and the water column pressure are negligible, , (2) liquid saturation is 100% behind the imbibition front (and thus the influence of liquid saturation on capillary pressure is not considered), and (3) the modified Lucas–Washburn model is applicable only if the transient imbibition volume correlates linearly with the square root of time, analogous to flow-regime identification in rate transient analysis …”

“…(3) the modified Lucas−Washburn model is applicable only if the transient imbibition volume correlates linearly with the square root of time, analogous to flow-regime identification in rate transient analysis. 47 For the one-directional linear flow inside tight and shale core plugs, the driving forces are the capillary pressure and ambient air�the vacuum pressure difference; the resistant force is the viscous force. Therefore, according to the Young−Laplace equation (eq 1) and Darcy's Law (eq 2)…”

“…1,46 Moreover, the permeability can be estimated from the field-scale production/pressure data based on the rate/pressure transient analysis theory, while the estimated permeability is only an average value under the combined influences of the formation matrix and fractures, production/ pressure data fluctuation, engineering operations, etc. 47 Vacuum imbibition has been recently used to determine the organic and inorganic porosities in crushed shale samples, 48 and numerical models have been developed to estimate organic and inorganic permeabilities and the associated fluid-transport mechanisms. 49,50 However, the application of this methodology for measuring the liquid permeability in tight and shale core plugs has challenges that need to be addressed.…”

“…Conventional permeability determination methods mainly include steady- and unsteady-state measurements. − The steady-state permeability is measured when the fluid flow reaches a stable rate under a constant pressure drop across the core plug, and the underlying theory is Darcy’s Law; the advantage of the steady-state method is the simplicity of data interpretation, while the disadvantages are the inaccuracy of the measured flow rate and the difficulty in the judgment of the true steady state for the low-permeability core plugs. , In contrast, for the unsteady-state measurement, a pressure pulse is applied at the upstream region of the core plug; afterward, the upstream and downstream pressure responses are monitored simultaneously until a pressure equilibrium is reached; , the unsteady-state permeability is then determined by the fitting between the pressure/time signal and the derived numerical/analytical model; the advantage of this method is the accuracy of the measured pressure signal, while the disadvantage of this method is the complexity of data interpretation. , In addition, permeability can also be estimated by the pore geometry; − the most classic one is the Carman–Kozeny permeability of 1 C CK L CK 2 ε β 3 (where C CK is the Carmen–Kozeny constant, L CK is the volumetric surface area, and ε β is the porosity), while the pore geometry method is unable to incorporate the effects of the solid–liquid interactions. , Moreover, the permeability can be estimated from the field-scale production/pressure data based on the rate/pressure transient analysis theory, while the estimated permeability is only an average value under the combined influences of the formation matrix and fractures, production/pressure data fluctuation, engineering operations, etc …”

Fracture Spacing Optimization Method for Multi-Stage Fractured Horizontal Wells in Shale Oil Reservoir Based on Dynamic Production Data Analysis

“…The above studies [16][17][18][19][20][21] proposed some new inversion methods of dynamic production data or improved the existing methods for interpretating reservoir parameters or fracture parameters after fracturing, and a certain theoretical basis for the dynamic production data inversion technology of multi-stage fractured horizontal wells was provided. However, due to the dramatic changes in flow pressure and the production rate in unconventional oil and gas production data with large errors [22], the normalized typical data points in the above dynamic production data inversion method were scattered, smooth typical curves were difficult to obtain and the data fitting effect was also poor, which resulted in great uncertainty in the fitting results. In addition, the interpreted post-hydraulic fracturing models of seepage flow during production in the aforementioned studies was rarely further applied to the optimization of productivity enhancement in the oil field.…”