Giant Carbonate Reservoir Study Showing Impact of Capillary Pressure Hysteresis on History Match & Field Development Plan

Author(s):  
Ahmed M. Ismail ◽  
Mohamed Zubair Kalam ◽  
Majdolin Hanna Jasser
2021 ◽  
Author(s):  
Basel AL-Otaibi ◽  
Issa Abu Shiekah ◽  
Manish Kumar Jha ◽  
Gerbert de Bruijn ◽  
Peter Male ◽  
...  

Abstract After 40 years of depletion drive, a mature, giant and multi-layer carbonate reservoir is developed through waterflooding. Oil production, sustained through infill drilling and new development patterns, is often associated with increasingly higher water production compared to earlier development phases. A field re-development plan has been established to alleviate the impact of reservoir heterogeneities on oil recovery, driven by the analysis of the historical performance of production and injection of a range of well types. The field is developed through historical opportunistic development concepts utilizing evolving technology trends. Therefore, the field has initially wide spacing vertical waterflooding patterns followed by horizontal wells, subjected to seawater or produced water injection, applying a range of wells placement or completion technologies and different water injection operating strategies. Systematic categorization, grouping and analyzing of a rich data set of wells performance have been complemented and integrated with insights from coarse full field and conceptual sector dynamic modeling activities. This workflow efficiently paved the way to optimize the field development aiming for increased oil recovery and cost saving opportunities. Integrated analysis of evolving historical development decisions revealed and ranked the primary subsurface and operational drivers behind the limited sweep efficiency and increased watercut. This helped mapping the impact of fundamental subsurface attributes from well placement, completion, or water injection strategies. Excellent vertical wells performance during the primary depletion and the early stage of water flooding was slowly outperformed by a more sustainable horizontal well production and injection strategy. This is consistent with a conceptual model in which the reservoir is dominated by extensive high conductive features that contributed in the early life of the field to good oil production before becoming the primary source of premature water breakthrough after a limited fraction of pore volume water was injected. The next level of analysis provided actual field evidence to support informed decisions to optimize the front runner horizontal wells development concept to cover wells length, orientation, vertical placement in the stratigraphy, spacing, pattern strategy and completion design. The findings enabled delivering updated field development plan covering the field life cycle to sustain and increase field oil production through adding ~ 200 additional wells and introducing more structured water flooding patterns in addition to establishing improved wells reservoir management practices. This integrated study manifests the power, efficiency and value from data driven analysis to capture lessons learned from evolving wells and development concepts applied in a complex brown field over six decades. The workflow enabled the delivery of an updated field development plan and production forecasts within a year through utilizing data analytics to compensate for the recognized limitations of subsurface models in addition to providing input to steer the more time-consuming modeling activities.


Author(s):  
A. Chaterine

This study accommodates subsurface uncertainties analysis and quantifies the effects on surface production volume to propose the optimal future field development. The problem of well productivity is sometimes only viewed from the surface components themselves, where in fact the subsurface component often has a significant effect on these production figures. In order to track the relationship between surface and subsurface, a model that integrates both must be created. The methods covered integrated asset modeling, probability forecasting, uncertainty quantification, sensitivity analysis, and optimization forecast. Subsurface uncertainties examined were : reservoir closure, regional segmentation, fluid contact, and SCAL properties. As the Integrated Asset Modeling is successfully conducted and a matched model is obtained for the gas-producing carbonate reservoir, highlights of the method are the following: 1) Up to ± 75% uncertainty range of reservoir parameters yields various production forecasting scenario using BHP control with the best case obtained is 335 BSCF of gas production and 254.4 MSTB of oil production, 2) SCAL properties and pseudo-faults are the most sensitive subsurface uncertainty that gives major impact to the production scheme, 3) EOS modeling and rock compressibility modeling must be evaluated seriously as those contribute significantly to condensate production and the field’s revenue, and 4) a proposed optimum production scenario for future development of the field with 151.6 BSCF gas and 414.4 MSTB oil that yields a total NPV of 218.7 MMUSD. The approach and methods implemented has been proven to result in more accurate production forecast and reduce the project cost as the effect of uncertainty reduction.


2016 ◽  
Vol 18 (1) ◽  
pp. 39-53
Author(s):  
Omar Salih ◽  
Mahmoud Tantawy ◽  
Sayed Elayouty ◽  
Atef Abd Hady

2021 ◽  
Author(s):  
Danhua Leslie Zhang ◽  
Xiaodong Shi ◽  
Chunyan Qi ◽  
Jianfei Zhan ◽  
Xue Han ◽  
...  

Abstract With the decline of conventional resources, the tight oil reserves in the Daqing oilfield are becoming increasingly important, but measuring relative permeability and determining production forecasts through laboratory core flow tests for tight formations are both difficult and time consuming. Results of laboratory testing are questionable due to the very small pore volume and low permeability of the reservoir rock, and there are challenges in controlling critical parameters during the special core analysis (SCAL) tests. In this paper, the protocol and workflow of a digital rock study for tight sandstones of the Daqing oilfield are discussed. The workflow includes 1) using a combination of various imaging methods to build rock models that are representative of reservoir rocks, 2) constructing digital fluid models of reservoir fluids and injectants, 3) applying laboratory measured wettability index data to define rock-fluid interaction in digital rock models, 4) performing pore-scale modelling to accelerate reservoir characterization and reduce the uncertainty, and 5) performing digital enhanced oil recovery (EOR) tests to analyze potential benefits of different scenarios. The target formations are tight (0.01 to 5 md range) sandstones that have a combination of large grain sizes juxtaposed against small pore openings which makes it challenging to select an appropriate set of imaging tools. To overcome the wide range of pore and grain scales, the imaging tools selected for the study included high resolution microCT imaging on core plugs and mini-plugs sampled from original plugs, overview scanning electron microscopy (SEM) imaging, mineralogical mapping, and high-resolution SEM imaging on the mini-plugs. High resolution digital rock models were constructed and subsequently upscaled to the plug level to differentiate bedding and other features could be differentiated. Permeability and porosity of digital rock models were benchmarked against laboratory measurements to confirm representativeness. The laboratory measured Amott-Harvey wettability index of restored core plugs was honored and applied to the digital rock models. Digital fluid models were built using the fluid PVT data. A Direct HydroDynamic (DHD) pore-scale flow simulator based on density functional hydrodynamics was used to model multiphase flow in the digital experiments. Capillary pressure, water-oil, surfactant solution-oil, and CO2-oil relative permeability were computed, as well as primary depletion followed with three-cycle CO2 huff-n-puff, and primary depletion followed with three-cycle surfactant solution huff-n-puff processes. Recovery factors were obtained for each method and resulting values were compared to establish most effective field development scenarios. The workflow developed in this paper provides fast and reliable means of obtaining critical data for field development design. Capillary pressure and relative permeability data obtained through digital experiments provide key input parameters for reservoir simulation; production scenario forecasts help evaluate various EOR methods. Digital simulations allow the different scenarios to be run on identical rock samples numerous times, which is not possible in the laboratory.


2021 ◽  
Author(s):  
Hung Vo Thanh ◽  
Kang-Kun Lee

Abstract Basement formation is known as the unique reservoir in the world. The fractured basement reservoir was contributed a large amount of oil and gas for Vietnam petroleum industry. However, the geological modelling and optimization of oil production is still a challenge for fractured basement reservoirs. Thus, this study aims to introduce the efficient workflow construction reservoir models for proposing the field development plan in a fractured crystalline reservoir. First, the Halo method was adapted for building the petrophysical model. Then, Drill stem history matching is conducted for adjusting the simulation results and pressure measurement. Next, the history-matched models are used to conduct the simulation scenarios to predict future reservoir performance. The possible potential design has four producers and three injectors in the fracture reservoir system. The field prediction results indicate that this scenario increases approximately 8 % oil recovery factor compared to the natural depletion production. This finding suggests that a suitable field development plan is necessary to improve sweep efficiency in the fractured oil formation. The critical contribution of this research is the proposed modelling and simulation with less data for the field development plan in fractured crystalline reservoir. This research's modelling and simulation findings provide a new solution for optimizing oil production that can be applied in Vietnam and other reservoirs in the world.


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