PRE-STACK SEISMIC INVERSION BASED ON A GENETIC ALGORITHM: A CASE FROM THE LLANOS BASIN (COLOMBIA) IN THE ABSENCE OF WELL INFORMATION

Abstract

The Llanos basin is the most prolific of the Colombian basins; however few stratigraphic plays have been explored due to the uncertainty in determining the lithology of the channels. Inside a migrated 2D section, a wide channel was identified inside a prospective sandy unit of the Carbonera Formation, composed by intercalations of sand and shale levels, and considered a main reservoir in this part of the basin. However, the lithology filling the channel was unknown due to the absence of wells. To infer the channel lithology, and diminish the prospective risk a model based pre-stack seismic inversion was proposed. However, without well logs available along the line, the uncertain initial model diminishes reliance on the inversion. To circumvent this impasse, a seismic inversion with a genetic algorithm was proposed. The algorithm was tested on synthetic seismograms and real data from an area of the basin, where well logs were available. The error analysis between the expected and the inverted results, in both scenarios, pointed out a good algorithmic performance. Then, the algorithm was applied to the pre stack data of the 2D line where the channel had been identified. According to the inverted results and rock physics analysis of wells near the seismic line with comparative geology, classified the channel was described as to be filled by silt, shale and probably some levels of shaly sands, increasing the exploratory risk because this lithology has low porosity and permeability, contrary to the producing reservoirs in neighbor fields, characterized by clean sands of high porosity. The algorithm is useful in areas with few or no borehole logs.