1 کارشناس ارشد مهندسی اکتشاف نفت، دانشکده مهندسی معدن، پردیس دانشکدههای فنی، دانشگاه تهران
2 دانشیار، گروه فیزیک زمین، مؤسسة ژئوفیزیک دانشگاه تهران، ایران
3 دانشیار، دانشکده مهندسی معدن، پردیس دانشکدههای فنی، دانشگاه تهران
4 کارشناس ارشد مهندسی اکتشاف نفت، شرکت نفت فلات قاره ایران
عنوان مقاله [English]
AVO theory was introduced around 20 years ago. In recent years, this technique was become to a major tool in hydrocarbon sources exploration. By the help of this method with the suitable understanding from underground layers and knowing how to use this technology, quantitative specifications of reservoir can be recognized.
AVO analysis is a seismic technique that by using of pre-stack data, establish the presence of hydrocarbon in reservoir. Three basic physical parameters used in seismic interpretation are density, P-wave velocity and S-wave velocity. For applying AVO technique, having a correct understanding of this parameters is required.
Introduction: Zoeppritz equations determine Reflection and Transmission Coefficients as a function of Incidence angle, but these equations don’t show how amplitude variations change with rock physical parameters truly. Zoeppritz equations approximations are simpler and more general respect to real equations. Some famous approximations for Zoeppritz equations are Aki, Richards & Fraiser (1980), Shuey and Fatti et al. approximations. With the help of these approximations some variable attributes can be extracted.
Ghar reservoir characterizations in Aboozar oil field: Aboozar oil field is located in North-West of Persian Gulf and is 75 KM far from east of Khark Island. This field was explored in recent 1950s and its production was started in 1976. The main hydrocarbon producer layer in this field is Ghar sand stone reservoir with Oligo-Miocene age. It has an anticline structure and is alongside in north-west south-east direction. Its depth is between 820 to 880 meters. This sand stone layer is corresponded to Ahvaz sand stone member in Asmari formation.
AVO analysis in Ghar sand stone reservoir: In this paper, different techniques that are involved in AVO analysis such as Forward Modeling, Fluid Replacement Modeling (FRM), various attribute extraction and X-Plot techniques are applied in Ghar sand stone reservoir to investigate the ability of AVO method for detection of light hydrocarbon in north-west of Persian Gulf. This study was done over a seismic line crossing a well in Aboozar Field. Some well logs data that are required for Forward Modeling in this well were available such as Density, P-wave and S-wave logs.
Forward Modeling: AVO modeling applied for investigation of Amplitude Versus Offset (AVO) variations and detection of parameters that produce these variations. With the help of available logs and by usage of Zoeppritz equations and Ray Tracing, synthetic seismogram in the well was produced. After producing of primary synthetic seismogram, significant reflections on real seismic data and synthetic seismogram were compared. By Forward Modeling the time-depth curve of the well was modified and seismic data were calibrated. Then on the produced synthetic seismogram in upper boundary of Ghar sand stone reservoir, AVO curve that show variations of Reflection Coefficients versus Offsets was extracted. This curve shows that AVO anomaly from upper boundary of Ghar sand stone reservoir is a class IV type which has a positive Gradient (B) and negative Intercept (A). Class IV type is corresponded to a gas sand stone with low Acoustic Impedance. Amplitudes were decrease versus offset in upper part of the reservoir.
Fluid Replacement Modeling (FRM): In this step, to verify AVO anomalies from Ghar reservoir, FRM was applied in the well area to satisfy anomalies related to fluid and mostly affected by gas. With the help of FRM, the best attributes for identification of Ghar reservoir upper boundary were distinguished. These attributes are related mostly to intergranular fluid. The base of FRM is Gassmann equation. For this purpose, 3 logs (P-wave velocity, S-wave velocity and density) in 3 fluid situations (real situation, 100% water saturation and 80% gas - 20% water saturation) were calculated and synthetic seismograms were produced.
AVO attributes study in seismic data: The time-sections of AVO attributes were extracted for real seismic data to use them for identification of AVO anomalies. Some of attributes are Gradient (B), Intercept (A), S-wave Reflection Coefficient (Rs), P-wave Reflection Coefficient (Rp) and Poisson Ratio Variations (??). From extracted attributes, Intercept (A) and Poisson Ratio Variations (??) attributes show the reservoir area more accurate. Also Poisson Ratio Variations (??) section has most variations in upper boundary of Ghar reservoir and identify the reservoir area more precise. On the Gradient (B) attribute section, the upper boundary of Ghar sand stone has negative values and by the help of Intercept (A) and Gradient (B), the type of AVO anomaly was distinguished.
(a) Intercept (A) versus Gradient (B) X-Plot by synthetic seismogram from well data
Intercept versus Gradient X-Plot can be use for interpretation of AVO analysis. It is a technique for classification of AVO responses and hydrocarbon sediment identification. By usage of rock physic parameters, AVO modeling and X-plot technique, AVO anomalies polarity can be analyzed. X-plot technique was applied for separation of reservoir fluids on real seismic data and synthetic seismogram from well data. A 100 mille-second window was considered on the synthetic seismogram at the Ghar reservoir area to use its related points in producing X-Plot Intercept versus Gradient. In the resulted X-Plot, most of points show a wet trend (in direction of second & fourth quarter). The rest points which are trended toward first and third quarter show the hydro carbon section.
(a) Intercept (A) versus Gradient (B) X-Plot by real seismic data
The X-Plots are powerful technique for separation of different zones with different fluid content and lithology. To obtain more accurate results and determine precise boundaries of reservoir, the X-Plot were done on the seismic line between 200 and 300 X-lines. The mentioned X-Plot was produced in a 150 mille-second window which is symmetric to 750 mille-second time limit (time limit of upper boundary of Ghar sand stone). This X-Plot enables us to separate reservoir section. According to obtained points, three zones were determined as bellow:
- Water zone trended to bisector of first and third quarters.
- First hydrocarbon zone in upper part of reservoir.
- Second hydrocarbon zone in lower part of reservoir and top of water zone.
Results obtained from this X-Plot are best-correlated to results of well seismogram X-Plot.
Conclusion: The purpose of this paper is identification of AVO method abilities in exploration of hydrocarbon reservoirs using pre-stack seismic data at north-west areas of Persian Gulf. The results of this study truly reveal these abilities. For this purpose, synthetic seismogram of well logging data produced for Aboozar oil field using Forward Modeling and with the help of that the reason of observed anomalies on pre-stack seismic data was detected at the upper boundary of Ghar reservoir. With producing AVO curve, the related anomaly type which is class IV, was determined. In this step, the time-depth curve was corrected by matching well and seismic data and the seismic data were calibrated.
In Forward Modeling step, well logging data were produced synthetically using Fluid Replacement Modeling (FRM) and with the help of synthetic seismogram and extraction of different attributes in 3 different fluids situations (real situation, 100% water saturation and 80% gas - 20% water saturation), the most suitable fluid affected attributes, which are able to distinguish the upper boundary of Ghar reservoir, were determined. These attributes are as following: Intercept (A) attribute, attribute of Poisson Ratio Variations (??), attribute of P-wave Reflection Coefficient and A×Sign (B) attribute.
In this study, AVO attributes were extracted from real seismic data using different methods. The most suitable attributes which enable us to distinguish reservoir boundaries were determined and a suitable correlation observed between these attributes and results obtained from Forward Modeling. With the help of different attributes, X-Plots of Intercept (A) versus Gradient (B) were produced in reservoir area. By usage of these plots, hydrocarbon limited area was separated in lower and upper sections of reservoir which had a well matching comparison to results obtained from X-Plot of Intercept (A) versus Gradient (B) of synthetic seismogram in reservoir area.