In this paper we apply the streamline-based production data integration method to condition a multimillion cell geologic model to historical production response for a giant Saudi Arabian reservoir. The field has been under peripheral water injection with 16 injectors and 70 producers. There is also a strong aquifer influx into the field. A total of 30 years of production history with detailed rate, infill well and reperforation schedule were incorporated via multiple pressure updates during streamline simulation. Also, gravity and compressibility effects were included to account for water slumping and aquifer support. To our knowledge, this is the first and the largest such application of production data integration to geologic models accounting for realistic field conditions. We have developed novel techniques to analytically compute the sensitivities of the production response in the presence of gravity and changing field conditions. This makes our method extremely computationally efficient. For the field application, the production data integration is carried out in less than 6 hours in a PC.The geologic model derived after conditioning to production response was validated using field surveillance data. In particular, the flood front movement, the aquifer encroachment and bypassed oil locations obtained from the geologic model was found to be consistent with field observations. Finally, an examination of the permeability changes during production data integration revealed that most of these changes were aligned along the facies distribution, particularly the 'good' facies distribution with no resulting loss in geologic realism. TX 75083-3836, U.S.A., fax 01-972-952-9435.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractA fine-scale full-field multimillion cell geologic model of a giant Saudi Arabian carbonate reservoir has been successfully conditioned to a thirty-year production/injection history. This represents the first worldwide case study of the technique for such a complicated reservoir with extensive flow history. The initial geologic model was created based on logderived porosity data, facies information, and a 3-d stochastic seismic inversion model. It was generated geostatistically using a sequential Gaussian simulation with collocated cokriging algorithm. It was desired to condition this initial model based on a thirty-year injection/production history.Fast streamline simulations were performed on the geological porosity and permeability models using field injection/production constraints.The flow conditioning algorithm iteratively modified the permeability field such that simulated injection/production behavior more closely approached the supplied injection/production history. The algorithm uses analogies to seismic travel time and tomography, involving iterative linearization of the time-offlight expression about a known initial model based on static data.The final flow conditioned model was then validated using more thorough streamline simulations verifying improvements in the match of the simulated injection/production response to that of the historical response. Additionally, inspection of the difference between the initial and the flow-conditioned final model showed permeability modifications followed a strong directional trend consistent with well-known geological trends. Results from the final conditioned models showed more than 30% improvement in terms of history-matching than that of initial model.
An innovative fracture modeling process has been successfully developed and utilized in a giant Saudi Arabian fracture carbonate reservoir. This modeling process constrains the discrete fractures to sets of geologic drivers describing the fracture relationships to reservoir matrix properties such as porosity, lithology and stylolites as well as to structural attributes including faults and curvature. The reservoir has very good matrix permeability, but it is enhanced significantly by faults, fractures and strataform. The workflow starts with the construction of a stochastic discrete fracture network generated in a given simulation volume by providing the static distribution of all relevant fracture parameters from image and core logs and geologic drivers. The fracture distribution is then validated in wells with the fracture counts from image logs and cores. The fracture counts from the model were found to give a consistent magnitude with the observed fracture counts in core and image logs in more than 70% match. The fracture network is then translated into fracture properties by incorporating geo-mechanical in-situ stress information including direction, magnitude, and vertical gradient to identify open fracture and to determine the effective fracture aperture. Due to high matrix permeability a representation of the matrix and strataform was incorporated with the fractures to produce a discrete feature model of the combined fracture/matrix system. This is essentially single medium model was used to calibrate against well-test data. Single flow simulation was then performed for the discrete feature model on each of the cells in the model. The calculated fracture properties include fracture permeability, fracture porosity, and the transfer function (sigma) measuring the interaction between the matrix and the fracture. The dynamic behavior of the simulated fracture permeability compared well to the Kh from pressure buildup tests. Results were very encouraging, as it appeared that in general, the fracture distribution in the reservoir had been properly described. Moreover, calibration of the fracture parameters such as permeability to match the observed dynamic behavior proved to be an effective way to achieve history match of both pressure and water cut, as was seen from simulation models using both dual porosity dual permeability and single porosity single permeability modeling techniques. Introduction Many large oil and gas reservoirs in the Middle East are fractured with varying degrees. This represents challenges in optimum reservoir development. Loss circulation while drilling and early water breakthroughs are a few among the most common problems encountered in these reservoirs. Yet, the development of a reliable fracture model is very difficult to achieve. In the non-fractured (conventional) reservoirs, permeability is dependent on the composition of the matrix. Where as in the fractured reservoir this is not the case. For example, the presence of a fault may substantially increase the permeability in a localized area. The challenge in fracture modeling is to define factors that control fractures and use them to generate a 3-D fracture model.
A new technique is developed for modeling 3D permeability distributions. The technique integrates all available data into a fluid flow simulation model. The integrated modeling process honors the essential aspects of the established reservoir descriptions as well as the geological facies model and engineering data. The added value of data integration of the fluid flow simulation is illustrated by the improved accuracy of the resulting well performance predictions and the decrease in time requirements for reservoir modeling history matching. The technique utilizes diverse data at different scales to condition reservoir models of facies, porosity, and permeability. Such data includes 3D seismic, well logs, core measurements, geologic facies distribution, flow meter logs, and pressure buildup tests. The model building process explicitly accounts for the difference in scale of the various measurements. The model calculates the porosity, facies, and permeability in the inter well volume using geostatistical techniques that are constrained by seismic impedance derived from the 3D seismic data. The use of engineering data in the permeability modeling constrains the results and decreases the history matching time requirements. A case study demonstrates the modeling technique. A reservoir model is developed for the Unayzah Formation in the Hawtah Field of Saudi Arabia. The Unayzah is a highly stratified clastic reservoir in a mixed fluvial and eolian depositional environment. Data integration provided more realistic reservoir model for this complex geologic setting than the conventional approach. Specifically, the integrated approach provide a reservoir model that captured the complex and highly stratified nature of the lithological units. Fluid flow simulation was carried out for both the new integrated reservoir model and the conventional reservoir model. Results show tremendous savings in history matching time and more accurate results for use in reservoir management production strategies when applying the new technique.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.