Determination, of Reservoir Permeability From Repeated Induction Logging

1991 ◽  
Vol 6 (01) ◽  
pp. 20-26 ◽  
Author(s):  
D.P. Tobola ◽  
S.A. Holditch
Keyword(s):  
Reservoir Permeability ◽  
Induction Logging

Statistical determination of geophysical well log response functions

Geophysics ◽  
1983 ◽  
Vol 48 (11) ◽  
pp. 1525-1535 ◽  
Author(s):  
Eugene A. Nosal
Keyword(s):  
Power Spectrum ◽  
Response Function ◽  
System Response ◽  
General Terms ◽  
Induction Logging ◽  
Conductivity Profile ◽  
Statistical Determination ◽  
The One

The vertical response function of induction logging tools is shown to be derivable from a power spectrum analysis of the measurement. The vertical response function is the one‐dimensional sequence of weights that characterizes how the tool combines the rock conductivities along the borehole to form an output called the apparent conductivity; it is the system impulse response. The value of knowing this function lies in the possible use of filter theory to aid in data processing and interpretation. Two general notions establish the framework for the analysis. The first is that logging is a linear, convolutional operation. Second, the earth’s conductivity profile forms a stochastic process. The probabilistic component is fleshed out by reasonably based assumptions about the occurrence of bed boundaries and nature of conductivity changes across them. Brought together, these tenets create a characterization of the conductivity sequence that is not a stationary process, but rather is intrinsic, as defined in the discipline of geostatistics. Such a process is described by a variogram, and it is increments of the process that are stationary. The connection between the power spectrum of the measurement and the system response function is made when the convolutional model is merged with the conductivity process. Some examples of induction log functions are shown using these ideas. The analysis is presented in general terms for possibly wider application.

scholarly journals PROCESSING OF OIL WELL PRESSURE RECOVERY CURVES

2019 ◽  
pp. 18-20
Author(s):  
Abasova Inara Afrail
Keyword(s):  
Numerical Simulation ◽  
Mathematical Model ◽  
Pressure Recovery ◽  
Oil Well ◽  
Recovery Curve ◽  
Recovery Curves ◽  
Reservoir Permeability ◽  
Curve Change ◽  
Industry Conditions

In the article the development of a mathematical model describing the PRC is studied on the base of pressure recovery curve method.Detailed processing of the pressure recovery curve made it possible to determine the deterioration of reservoir permeability in many wells. Here two methods are considered - stationary (steady conditions of selection) and non- stationary.The article proves that the use of these methods allows to develop a mathematical model to increase the determination of this task.On the base of numerical simulation, the following facts had impact on the results of the pressure recovery curve: well shutdown time, taking into account the initial transition section, taking into account curve change section before well shutdown.The study of variable factors impact on the results is carried out by interval estimation.The mathematical model describing the pressure recovery curve is local and changes its structures. This model can be used in industry conditions.

Novel transient multicomponent induction logging method for the determination of dip angle and anisotropy of formation

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. D181-D197
Author(s):  
Xiyong Yuan ◽  
Shaogui Deng ◽  
Yiren Fan ◽  
Xufei Hu ◽  
Zhenguan Wu ◽  
...  
Keyword(s):  
Coordinate System ◽  
Measurement Errors ◽  
Dipole Moments ◽  
Algebraic Method ◽  
Inversion Process ◽  
True Value ◽  
Induction Logging ◽  
Dip Angle ◽  
Source Dipole

The relative dip angle and anisotropy of the anisotropic formation are generally determined through an inversion process. We have studied the responses of the novel transient multicomponent induction logging method and find that all of the components measured in the instrument coordinate system have the same decay with time. However, the cross component decays much faster than the coaxial or coplanar components in the formation coordinate system. We adopt an algebraic time-domain method to calculate the dip angle and anisotropy coefficient and thereby avoid the inversion process. The accuracy and applicability of this pseudoinversion method are studied theoretically. Numerical results demonstrate that coaxial, coplanar, and cross components are used to calculate the apparent relative dip angle that yields the exactly true value at very early times and then goes through a transition deviating from the true dip and gradually approaches the true value again at late times. The apparent anisotropy is calculated by the coaxial and coplanar components and is equal to zero at early times and nonzero to the true anisotropy during the transition times. Moreover, by using realistic source dipole moments as well as adding random measurement errors, the practicality of this algebraic method is also investigated. Determination of the relative dip is still stable and valid. Determination of the anisotropy is more easily affected by measurement error and has some application limitations.

scholarly journals Oil Reservoir Permeability Estimation from Well Logging Data Using Statistical Methods (A Case Study: South Pars Oil Reservoir)

2017 ◽  
Vol 3 (10) ◽  
pp. 831 ◽  
Author(s):  
Akbar Esmailzadeh ◽  
Sina Ahmadi ◽  
Reza Rooki ◽  
Reza Mikaeil
Keyword(s):  
Nonlinear Models ◽  
Accurate Determination ◽  
Well Logging ◽  
Oil Reservoir ◽  
Well Test ◽  
Sonic Log ◽  
Reservoir Permeability ◽  
Factor Log ◽  
Resistivity Log

Permeability is a key parameter that affects fluids flow in reservoir and its accurate determination is a significant task. Permeability usually is measured using practical approaches such as either core analysis or well test which both are time and cost consuming. For these reasons applying well logging data in order to obtaining petrophysical properties of oil reservoir such as permeability and porosity is common. Most of petrophysical parameters generally have relationship with one of well logged data. But reservoir permeability does not show clear and meaningful correlation with any of logged data. Sonic log, density log, neutron log, resistivity log, photo electric factor log and gamma log, are the logs which effect on permeability. It is clear that all of above logs do not effect on permeability with same degree. Hence determination of which log or logs have more effect on permeability is essential task. In order to obtaining mathematical relationship between permeability and affected log data, fitting statistical nonlinear models on measured geophysical data logs as input data and measured vertical and horizontal permeability data as output, was studied. Results indicate that sonic log, density log, neutron log and resistivity log have most effect on permeability, so nonlinear relationships between these logs and permeability was done.

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