Waveform inversion of poststacked reflection seismic data with well log constrained using nonlinear optimization methods

Abstract Surface reflection seismic inversion techniques are currently applied by the industry for mapping the rock physical properties of oil reservoirs. This information permits speeding up the interpretation process to ultimately provide well locations. At present, many companies require the inversion to be completed before any well is drilled. Inversion techniques can be applied to prestacked and poststacked seismic data. Prestacked data inversion is more complex than poststacked, but it provides more information for the interpreter (e.g., P-wave and S-wave impedances). On the other hand, poststacked inversion provides only the acoustic P-wave impedance. However, the main outcome of prestacked inversion is the increase in resolution when full waveforms are inverted. Currently, poststacked seismic inversion is used to correlate P-wave impedance with rock physical properties obtained from well logs. The logs are provided by a well near the survey line, allowing images of different rock properties to be processed and analyzed. We extend the use of the acoustic P-wave impedance by constraining it with the well lithology, consequently categorizing the impedance by classes (i.e., sand, shale, and limestone) and converting the impedance to earth properties using well logs and regression models. This process allows us to build a single initial estimate of the earth property model, which is iteratively refined to produce a synthetic seismogram (by means of forward modeling) to match the observed seismic data. The inversion algorithm that minimizes the misfits between observed and synthetic full-waveform data improves the P-wave velocity resolution. The interpreter can thus delineate thin channels (flow units saturated with hydrocarbons) that are undetected using current techniques.