poro-acoustic impedance as a new seismic inversion attribute for reservoir characterization

Porosity is one of the most important petrophysical parameters, studied in the subject of reservoir characterization. determining porosity and how it changes in hydrocarbon reservoirs is an important issue that has been addressed in various researches. in this research, poro-acoustic impedance (pai) is introduced as an extended form of acoustic impedance (ai). the difference between pai and ai is related porosity that is directly involved in the pai. the inclusion of porosity data in the pai formula made porosity effective in forward modeling and inversion of seismic data. the use of pai in the forward modeling of synthetic models increases the contrast between the subsurface layers, and the contrast increases twice as compared to the ai. band limited recursive inversion (blri) algorithm is used for inversion of synthetic seismograms and model-based algorithm is used for real seismic data inversion. for real data, due to the existence of well data, seismic horizons and geological information, using the basic model method for inversion is more accurate. the main difference between inversion using pai and ai is that changes in porosity can be seen directly in the results of pai inversion. the correlation of porosity with pai and ai is -0.93 and -0.85, respectively, which shows that porosity has a stronger relationship with pai. the use of pai can be a quick and simple solution to understand porosity changes in hydrocarbon reservoirs and increase the accuracy of porosity determination in reservoirs to a great extent.

poro-acoustic impedance as a new seismic inversion attribute for reservoir characterization

porosity is one of the most important petrophysical parameters, studied in the subject of reservoir characterization. determining porosity and how it changes in hydrocarbon reservoirs is an important issue that has been addressed in various researches. in this research, poro-acoustic impedance (pai) is introduced as an extended form of acoustic impedance (ai). the difference between pai and ai is related porosity that is directly involved in the pai. the inclusion of porosity data in the pai formula made porosity effective in forward modeling and inversion of seismic data. the use of pai in the forward modeling of synthetic models increases the contrast between the subsurface layers, and the contrast increases twice as compared to the ai. band limited recursive inversion (blri) algorithm is used for inversion of synthetic seismograms and model-based algorithm is used for real seismic data inversion. for real data, due to the existence of well data, seismic horizons and geological information, using the basic model method for inversion is more accurate. the main difference between inversion using pai and ai is that changes in porosity can be seen directly in the results of pai inversion. the correlation of porosity with pai and ai is -0.93 and -0.85, respectively, which shows that porosity has a stronger relationship with pai. the use of pai can be a quick and simple solution to understand porosity changes in hydrocarbon reservoirs and increase the accuracy of porosity determination in reservoirs to a great extent.