Inclusions of well test interpretation and sector model simulation into a full field model: an integration modeling approach

Author(s):  
Nasser Saqer Al-Mohannadi ◽  
Oliver Maximilian Seybold ◽  
Gert-jan C.A. Reijnders ◽  
Jean-Michel Laurent Dawans
GeoArabia ◽  
1996 ◽  
Vol 1 (2) ◽  
pp. 267-284
Author(s):  
John L. Douglas ◽  

ABSTRACT The North ‘Ain Dar 3-D geocellular model consists of geostatistical models for electrofacies, porosity and permeability for a portion of the Jurassic Arab-D reservoir of Ghawar field, Saudi Arabia. The reservoir consists of a series of shallow water carbonate shelf sediments and is subdivided into 10 time-stratigraphic slices on the basis of core descriptions and gamma/porosity log correlations. The North ‘Ain Dar model includes an electrofacies model and electrofacies-dependent porosity and permeability models. Sequential Indicator Simulations were used to create the electrofacies and porosity models. Cloud Transform Simulations were used to generate permeability models. Advantages of the geostatistical modeling approach used here include: (1) porosity and permeability models are constrained by the electrofacies model, i.e. by the distribution of reservoir rock types; (2) patterns of spatial correlation and variability present in well log and core data are built into the models; (3) data extremes are preserved and are incorporated into the model. These are critical when it comes to determining fluid flow patterns in the reservoir. Comparison of model Kh with production data Kh indicates that the stratigraphic boundaries used in the model generally coincide with shifts in fluid flow as indicated by flowmeter data, and therefore represent reasonable flow unit boundaries. Further, model permeability and production estimated permeability are correlated on a Kh basis, in terms of vertical patterns of distribution and cumulative Kh values at well locations. This agreement between model and well test Kh improves on previous, deterministic models of the Arab-D reservoir and indicates that the modeling approach used in North ‘Ain Dar should be applicable to other portions of the Ghawar reservoir.


DYNA ◽  
2019 ◽  
Vol 86 (210) ◽  
pp. 108-114
Author(s):  
Freddy Humberto Escobar ◽  
Angela María Palomino ◽  
Alfredo Ghisays Ruiz

Flow behind the casing has normally been identified and quantified using production logging tools. Very few applications of pressure transient analysis, which is much cheaper, have been devoted to determining compromised cemented zones. In this work, a methodology for a well test interpretation for determining conductivity behind the casing is developed. It provided good results with synthetic examples.


2007 ◽  
Vol 11 (4) ◽  
pp. 1323-1339 ◽  
Author(s):  
M. Konz ◽  
S. Uhlenbrook ◽  
L. Braun ◽  
A. Shrestha ◽  
S. Demuth

Abstract. The paper presents a catchment modeling approach for remote glacierized Himalayan catchments. The distributed catchment model TACD, which is widely based on the HBV model, was further developed for the application in highly glacierized catchments on a daily timestep and applied to the Nepalese Himalayan headwater Langtang Khola (360 km2). Low laying reference stations are taken for temperature extrapolation applying a second order polynomial function. Probability based statistical methods enable bridging data gaps in daily precipitation time series and the redistribution of cumulated precipitation sums over the previous days. Snow and ice melt was calculated in a distributed way based on the temperature-index method employing calculated daily potential sunshine durations. Different melting conditions of snow and ice and melting of ice under debris layers were considered. The spatial delineation of hydrological response units was achieved by taking topographic and physiographic information from maps and satellite images into account, and enabled to incorporate process knowledge into the model. Simulation results demonstrated that the model is able to simulate daily discharge for a period of 10 years and point glacier mass balances observed in the research area with an adequate reliability. The simple but robust data pre-processing and modeling approach enables the determination of the components of the water balance of a remote, data scarce catchment with a minimum of input data.


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