Evaluation of Hydrocarbon Potential Using AVO Analysis in the FORMAT Field, Niger Delta Basin, Nigeria

The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.

Reservoir prediction using pre-stack inverted elastic parameters

This is a case study of the application of pre-stack inverted elastic parameters to tight-sand reservoir prediction. With the development of oil and gas exploration, pre-stack data and inversion results are increasingly used for production objectives. The pre-stack seismic property studies include not only amplitude verse offset （AVO） but also the characteristics of other elastic property changes. In this paper, we analyze the elastic property parameters characteristics of gas- and wet-sands using data from four gas-sand core types. We found that some special elastic property parameters or combinations can be used to identify gas sands from water saturated sand. Thus, we can do reservoir interpretation and description using different elastic property data from the pre-stack seismic inversion processing. The pre- stack inversion method is based on the simplified Aki-Richard linear equation. The initial model can be generated from well log data and seismic and geologic interpreted horizons in the study area. The input seismic data is angle gathers generated from the common reflection gathers used in pre-stack time or depth migration. The inversion results are elastic property parameters or their combinations. We use a field data example to examine which elastic property parameters or combinations of parameters can most easily discriminate gas sands from background geology and which are most sensitive to pore-fluid content. Comparing the inversion results to well data, we found that it is useful to predict gas reservoirs using λ, λρ, λ/μ, and K/μ properties, which indicate the gas characteristics in the study reservoir.

Prediction of Coal Seam Methane Enriched Areas Using Seismic Data

All coal mine disasters are dynamic geological phenomenon and affected by many factors. However, locating the enriched areas of CSM (coal seam methane) may be the precondition for the successful prediction of such disasters. Traditional methods of investigating CSM enriched areas use limited data and only consider a few important factors. Their success rate is low and cannot meet practical needs. In this paper, an alternative method is proposed. The proce- dure is given as follows: 1) fracture attributes derived from azimuth variations of P-wave data in coal seams and wall rocks can be extracted; 2) AVO attributes, such as the intercept P and gradient G parameters can be extracted from different azimuths from 3D seismic data; 3) seismic cubes can be inverted and the relative attributes of imped- ance cubes can be extracted; 4) using a GIS platform, multi-source information can be obtained and analyzed; these include fracture attributes of coal seams and wall rocks, the thickness of coal seams, the distribution of faults and structures, the depth of coal seams, the inclination and exposure of coal seams and the coal rank. Through this processing procedure, methane enriched areas can be systematically detected.

Prospects delineation and evaluation using the CDP gathers characterization, onshore Nile Delta, Egypt

In the last decade, the seismic AVO analysis have become prominent in the direct hydrocarbons indicator(DHI), aimed at characterizing the fluid content or the lithology of a possible reservoir and reducing theexploration drilling risk. This research discuss the impact of studying the common depth point (CDP)gathers on Near, Mid and Far-offsets, to verify the credibility of the amplitude response in the prospectevaluation, through analyzing a case study of two exploratory wells;one has already penetrated a gasbearing sandstone as a reservoir and the other one is dry-sand, but drilled in two different prospects,using the amplitude versus offset (AVO) analysis, to understand the reservoir configuration and itsrelation to the different amplitude response. The results show, that the missing of the short-offset data isthe reason of the false anomaly encountered in the dry sand, due to some urban surface obstacles duringacquiring the seismic data in the field especially, the study area is located in El Mansoura city, which it isa highly cultivated flat terrain, with multiple channels and many large orchards on the edge of the river,and sugar cane and rice fields. Several lessons have been learned, which how to differentiate between thegas reservoirs and non-reservoirs, by understanding the relation between the Near and Far-offset traces,to reduce the amplitude anomalies to their right justification, where missing of Near-offset data led to apseudo-amplitude anomaly. The results led to a high success of exploration ratio as the positives vastlyoutweigh the negatives.