On: “A 3-D seismic case history evaluating fluvially deposited thin‐bed reservoirs in a gas‐producing property,” by B. A. Hardage, R. A. Levey, V. Pendleton, J. Simmons, and R. Edsen (November 1994 GEOPHYSICS, 59, p. 1650–1665).

Geophysics ◽  
1995 ◽  
Vol 60 (5) ◽  
pp. 1585-1587 ◽  
Author(s):  
Miodrag M. Roksandic

Hardage et al. (1994) conducted a study at Stratton Field with the purpose of detecting thin‐bed compartmented reservoirs in a fluvially deposited system (Oligocene Frio Formation), and rightly concluded that, in order to determine which seismically imaged stratigraphic changes are compartment boundaries, it is necessary to incorporate geologic and reservoir engineering data (particularly reservoir pressure data) into seismic interpretation. Their interpretation philosophy consisted of defining depositional stratal surfaces (I would rather say paleodepositional surfaces), and in analyzing seismic reflection amplitude behavior on such surfaces.

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1507-1519 ◽  
Author(s):  
B. A. Hardage ◽  
J. L. Simmons ◽  
V. M. Pendleton ◽  
B. A. Stubbs ◽  
B. J. Uszynski

A study was done at Nash Draw field, Eddy County, New Mexico, to demonstrate how engineering, drilling, geologic, geophysical, and petrophysical technologies should be integrated to improve oil recovery from Brushy Canyon reservoirs at depths of approximately 6600 ft (2000 m) on the northwest slope of the Delaware basin. These thin‐bed reservoirs were deposited in a slope‐basin environment by a mechanism debated by researchers, a common model being turbidite deposition. In this paper, we describe how state‐of‐the‐art 3-D seismic data were acquired, interpreted, integrated with other reservoir data, and then used to improve the sitting of in‐field wells and to provide facies parameters for reservoir simulation across this complex depositional system. The 3-D seismic field program was an onshore subsalt imaging effort because the Ochoan Rustler/Salado, a high‐velocity salt/anhydrite section, extended from the surface to a depth of approximately 3000 ft (900 m) across the entire study area. The primary imaging targets were heterogenous siltstone and fine‐grained sandstone successions approximately 100 ft (30 m) thick and comprised of complex assemblages of thin lobe‐like deposits having individual thickness of 3 to 6 ft (1 to 2 m). The seismic acquisition was complicated further by (1) the presence of active potash mines around and beneath the 3-D grid that were being worked at depths of 500 to 600 ft (150 to 180 m), (2) shallow salt lakes, and (3) numerous archeological sites. We show that by careful presurvey wave testing and attention to detail during data processing, thin‐bed reservoirs in this portion of the Delaware basin can be imaged with a signal bandwidth of 10 to 100 Hz and that siltstone/sandstone successions 100 ft (30 m) thick in the basal Brushy Canyon interval can be individually detected and interpreted. Further, we show that amplitude attributes extracted from these 3-D data are valuable indicators of the amount of net pay and porosity‐feet in the major reservoir successions and of the variations in the fluid transmissivity observed in production wells across the field. Relationships between seismic reflection amplitude and reservoir properties determined at the initial calibration wells have been used to site and drill two production wells. The first well found excellent reservoir conditions; the second well was slightly mispositioned relative to the targeted reflection‐amplitude trend and penetrated reservoir facies typical of that at other producing wells. Relationships between seismic reflection amplitude and critical petrophysical properties of the thin‐bed reservoirs have also allowed a seismic‐driven simulation of reservoir performance to be initiated.


2013 ◽  
Vol 53 (2) ◽  
pp. 473
Author(s):  
Nicholas Kwok

The Blasingame typecurve in Fekete’s Rate Transient Analysis (RTA) software has been used at Santos to increase the understanding and integration of well and reservoir data; however, the authors have discovered that in some cases the tool produced anomalous results, such as permeability being too low. The potential consequence of this was incorrectly writing off reserves or making projects (in particular compression projects) fail economic tests. After testing various hypotheses, a simple yet unorthodox solution was only discovered in a field where the anomaly was more profound, and required integrating geology and geophysics to explain it. This solution has since been applied in RTA models across numerous other fields, and it has improved the quality and confidence of these models. The solution was the realisation that in many cases the accessed gas in place (GIP) increased over time, but the underlying model in RTA assumes a single tank, linear P/z. Matching the RTA model with the initial reservoir pressure and final accessed GIP results in over-predicting the reservoir pressures, resulting in an artificially low permeability. The authors discovered that the appropriate well and reservoir parameters could be obtained by matching the late time data using a lower initial reservoir pressure value corresponding to when the well had accessed the final GIP volume but not the initial reservoir pressure. This step was initially regarded to be counter-intuitive as the initial pressure is a measured property. Numerous reviews have endorsed this methodology, which is now being used as a standard at Santos.


Geophysics ◽  
1963 ◽  
Vol 28 (6) ◽  
pp. 990-1000 ◽  
Author(s):  
L. Y. Faust

The seismic discovery of the Fargo Field, Wilbarger County, Texas, followed routine correlation procedures as practiced in 1936. Management contributed the policy of permitting record quality to determine the area explored. Gravity confirmed the seismic interpretation which was confirmed also in most details by subsequent wells. Seismic coverage averaged three townships per month at a cost of $28 per profile and $87 per square mile for the three‐mile square grids employed. The question is examined whether this comparatively low‐cost technique might be modernized into an effective reconnaissance tool. A line of the key data was transferred to magnetic tape (at some loss) and a few modern techniques employed. Compositing of these data was unpromising. Cross‐correlation of the composited data failed to yield sufficient improvement. A quasi‐continuous variable‐density presentation of 33 percent bed coverage shows the structure and provides some detail. The results suggest that further research might succeed in developing a useful method.


1974 ◽  
Vol 14 (01) ◽  
pp. 55-62 ◽  
Author(s):  
Hossein Kazemi

Abstract Two simple and equivalent procedures are suggested for improving the calculated average reservoir pressure from pressure buildup tests of liquid or gas wells in developed reservoirs. These procedures are particularly useful in gas well test procedures are particularly useful in gas well test analysis, irrespective of gas composition, in reservoirs with pressure-dependent permeability and porosity, and in oil reservoirs where substantial gas porosity, and in oil reservoirs where substantial gas saturation has been developed. A knowledge of the long-term production history is definitely helpful in providing proper insight in the reservoir engineering providing proper insight in the reservoir engineering aspects of a reservoir, but such long-term production histories need not be known in applying the suggested procedures to pressure buildup analysis. Introduction For analyzing pressure buildup data with constant flow rate before shut-in, there are two plotting procedures that are used the most: the procedures that are used the most: the Miller-Dyes-Hutchinson (MDH) plot and the Horner plot. The MDH plot is a plot of p vs log Deltat, whereas the Horner plot is a plot of p vs log [(t + Deltat)/Deltat]. Deltat is the shut-in time and t is a pseudoproduction time equal to the ratio of total produced fluid to last stabilized flow rate before shut-in. This method was first used by Theis in the water industry. Miller-Dyes-Hutchinson presented a method for calculating the average reservoir pressure, T, in in 1950. This method requires pseudosteady state before shut-in and was at first restricted to a circular reservoir with a centrally located well. Pitzer extended the method to include other Pitzer extended the method to include other geometries. Much later, Dietz developed a simpler interpretation scheme using the same MDH plot: p is read on the extrapolated straight-line section of the pressure buildup curve at shut-in time, Deltat,(1) where C is the shape factor for the particular drainage area geometry and the well location; values for C are tabulated in Refs. 5 and 13. For a circular drainage area with a centrally located well, C = 31.6, and for a square, C = 30.9.Horner presented another approach, which depended on the knowledge of the initial reservoir pressure, pi. This method also was first developed pressure, pi. This method also was first developed for a centrally located well in a circular reservoir.Matthews-Brons-Hazebroek (MBH) introduced another average reservoir pressure determination technique, which has been used more often than other methods: first a Horner plot is made; then the proper straight-line section of the buildup curve is proper straight-line section of the buildup curve is extrapolated to [(t + Deltat)/Deltat] = 1 (this intercept is denoted p*); finally, p is calculated from(2) m is the absolute value of the slope of the straightline section of the Horner plot:(3) pDMBH (tDA) is the MBH dimensionless pressure pDMBH (tDA) is the MBH dimensionless pressure at tDA, and tDA is the dimensionless time:(4) tp k a pseudoproduction time in hours:(5) PDMBH tDA) for different geometries and different PDMBH tDA) for different geometries and different well locations are given in Refs. 6 and 13.The second term on the right-hand side of Eq. 2 is a correction term for finite reservoirs that is based on material balance. Thus, for an infinite reservoir, p = pi = p*, where pi is the initial reservoir pressure. SPEJ P. 55


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