Fractured reservoir prediction from 3D seismic volumetric curvature and low‐frequency imaging

Author(s):  
D. Mike Buck ◽  
Aftab Alam ◽  
James D. Taylor
2011 ◽  
Author(s):  
Lifeng Liu ◽  
Sam Zandong Sun ◽  
Haiyang Wang ◽  
Haijun Yang ◽  
Jianfa Han ◽  
...  

2017 ◽  
Vol 25 (03) ◽  
pp. 1750022
Author(s):  
Xiuwei Yang ◽  
Peimin Zhu

Acoustic impedance (AI) from seismic inversion can indicate rock properties and can be used, when combined with rock physics, to predict reservoir parameters, such as porosity. Solutions to seismic inversion problem are almost nonunique due to the limited bandwidth of seismic data. Additional constraints from well log data and geology are needed to arrive at a reasonable solution. In this paper, sedimentary facies is used to reduce the uncertainty in inversion and rock physics modeling; the results not only agree with seismic data, but also conform to geology. A reservoir prediction method, which incorporates seismic data, well logs, rock physics and sedimentary facies, is proposed. AI was first derived by constrained sparse spike inversion (CSSI) using a sedimentary facies dependent low-frequency model, and then was transformed to reservoir parameters by sequential simulation, statistical rock physics and [Formula: see text]-model. Two numerical experiments using synthetic model and real data indicated that the sedimentary facies information may help to obtain a more reasonable prediction.


2021 ◽  
pp. 2250-2261
Author(s):  
Ahmed Muslim Khawaja ◽  
Jassim Muhammad Thabit

     This research is an attempt to solve the ambiguity associated with the stratigraphic setting of the main reservoir (late Cretaceous) of Mishrif Formation in Dujaila oil field. This was achieved by studying a 3D seismic reflection post-stack data for an area of ​​602.62 Km2 in Maysan Governorate, southeast of Iraq. Seismic analysis of the true amplitude reflections, time maps, and 3D depositional models showed a sufficient seismic evidence that the Mishrif Formation produces oil from a stratigraphic trap of isolated reef carbonate buildups that were grown on the shelf edge of the carbonate platform, located in the area around the productive well Dujaila-1. The low-frequency attribute illustrated that it is restricted in the area around the productive well Dujaila-1, which confirmed the existence of reef porous carbonate buildups and hydrocarbon accumulation in this region. The pay zone of the reef mound trap extends for about 7 km from the well Dujaila-1 toward the southwest side and 4 km toward the well Dujaila-2, without reaching it, which is explaining why it was dry. Therefore, this area to the south of the productive well Dujaila-1 represents a good area for low-risk drilling. Consequently, the hydrocarbon system observed in the Dujaila oil field provides a new opportunity to explore and produce oil in Mishrif Formation in other areas on the flank of the productive structures and in flat areas situated on the belt of the carbonate platform edge.


2020 ◽  
Vol 17 (3) ◽  
pp. 484-492 ◽  
Author(s):  
Faqi He ◽  
Ying Rao ◽  
Weihong Wang ◽  
Yanghua Wang

Abstract This paper presents a case study on the prediction of hydrocarbon reservoirs within coal-bearing formations of the Upper Palaeozoic. The target reservoirs are low-permeability low-pressure tight-sandstone reservoirs in the Daniudi Gas Field, Ordos Basin, China. The prime difficulty in reservoir prediction is caused by the interbedding coal seams within the formations, which generate low-frequency strong-amplitude reflections in seismic profiles. To tackle this difficulty, first, we undertook a careful analysis regarding the stratigraphy and lithology of these coal-bearing formations within the study area. Then, we conducted a geostatistical inversion using 3D seismic data and obtained reservoir parameters including seismic impedance, gamma ray, porosity and density. Finally, we carried out a reservoir prediction in the coal-bearing formations, based on the reservoir parameters obtained from geostatistical inversion and combined with petrophysical analysis results. The prediction result is accurately matched with the actual gas-test data for the targeted four segments of the coal-bearing formations.


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