Integrated Geological and Engineering Uncertainty Analysis Workflow, Lower Permian Carbonate Reservoir, Timan-Pechora Basin, Russia (Russian)

Shirazi, Abdi F.; Solonitsyn, Sergei; Kuvaev, Igor

doi:10.2118/136322-ru

Cited by 3 publications

(1 citation statement)

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“…The upscaling of the static model was based on preserving the most significant geological events and dynamic data, but flow tests were not included. [8] The calibration process of a simulator (history match) is quite time consuming. Techniques such as ensemble Kalman filter (EnKF) are presented to improve the match of observed data compared with manual history matching.…”

Section: Introductionmentioning

confidence: 99%

Toward robust history matching of a giant carbonate gas‐condensate reservoir

Ghadami

Rasaei

Hejri³

2015

Asia-Pacific J Chem Eng

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Carbonate reservoirs are highly heterogeneous and require considerable effort to characterize and model. This is because of complex depositional and diagenetic processes involved in their formation.This paper presents and discusses a systematic methodology that leads to a sound full-field dynamic model such that its behavior is closed to the field historical records without much interfering the model. The methodology was applied to a giant carbonate gas-condensate reservoir characterized by several heterogeneous layers. Sedimentology and sequence stratigraphy studies were performed to capture the heterogeneity and selection of geological zones and subzones.Prior to construction of the field simulation model, single-well modeling was conducted and tuned to well test data to target several objectives. These included evaluation of formation capacity (kh) and skin factor/non-Darcy effect as deducted from a match to drill stem test (DST) results. The effect of skin factor (S) and non-Darcy coefficient (D) on flow performance in the framework of sensitivity analysis was followed. Boost factors were obtained to upscale the core averaged kh to that of well test and used in the full-field dynamic model.The dynamic model was upscaled using production logging tool/DST data and incorporating the concept of hydraulic flow zone unit. The objective of tracking model coherency throughout the upscaling process was followed. The initial gas in place closely matched that of the static model. With the approach used in the current work, the data matching process took minimum effort. In addition, the model although of a relatively considerable size required short computing time for all forecast scenarios.

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Section: Introductionmentioning

confidence: 99%

Toward robust history matching of a giant carbonate gas‐condensate reservoir

Ghadami

Rasaei

Hejri³

2015

Asia-Pacific J Chem Eng

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Integrated Subsurface Uncertainty Study and Application - A Case Study of a Chalk Reservoir, Greater Ekofisk Area, North Sea

Sorensen

Sudan

et al. 2014

SPE Annual Technical Conference and Exhibition

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The concept of uncertainty, risk, and probabilistic assessment is increasingly employed as a standard in the E&P industry to assist in development and investment decisions. The Tor field in the Greater Ekofisk Area of the North Sea is a producing chalk field, which has a 35-year production history and aging facilities. This naturally fractured chalk reservoir has had limited water injection and experienced rapid decline. An integrated subsurface uncertainty study has been performed to support a potential redevelopment of the Tor field. This paper will demonstrate the integrated workflow for the uncertainty study and the methodologies used to overcome challenges in reservoir modeling and forecasting. The results of the sensitivity analysis and assisted history matching (AHM) process will be illustrated as well as how the results were applied in the evaluation of redevelopment options and in preparing future reservoir management plan. The main challenges in reservoir modeling, forecasting and overall evaluation of the Tor field are: 1) Uncertainties outside the well control area. This results in a significant structure uncertainty, hence an even more increased uncertainty in structural dependent properties. 2) Uncertainty and implementation of inter-dependent static properties and their spatial distribution. The deterministic base case model is only one of thousands of property realizations from the geostatistical modeling process. 3) Uncertainty and systematic implementation of effective permeability. Effective permeability in the chalk reservoir is a combination of enhanced matrix permeability and "highways". Predictability of potential "highways" not identified by existing wells is especially challenging. 4) Simulation time. These uncertainties will directly influence the determination of hydrocarbon in place, well placement, and waterflooding efficiency and add risk to the production forecast used to justify field redevelopment. The workflow was: 1) Identification and framing of uncertainty parameters. 2) Complete static and dynamic parameters analysis and integration. 3) Comprehensive sensitivity analysis and AHM. 4) Forecasting based on multiple calibrated models to reach the rigorous probabilistic production profiles. The approach used include: 1) Realization of structure uncertainty and associated properties by a robust approach, which is advantageous for the AHM process. 2) Employment of multiple property realizations. 3) Use of a 3D seismic attribute for capturing potential highways uncertainty and for systematic effective permeability implementation. 4) Addressing uncertainty in water flood sweep efficiency. From the integrated workflow and robust methodology, a suite of "good quality" AHM models with equal probability are obtained. AHM has narrowed down the uncertainty range and from post-AHM analysis the initial resource range and main influential parameters on development are determined. As one of the best practices, we recommend using across sampled representative models with well & operation uncertainties rather than a specific P10, P50 or P90 model to make final probabilistic forecasts.

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Automatic Well Completions and Reservoir Grid Data Quality Assurance for Reservoir Simulation Models

Al-Zahrani

Al-Mulla

Al-Nuaim

2015

Day 3 Wed, September 16, 2015

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Reservoir simulation engineers have to go through an intense and time consuming process to manually quality check large amounts of data which consist of wells, logs and completion events for more than 50 years of history. It is fundamental that data used in building reservoir simulation models is quality controlled and cross-checked to eliminate inconsistencies during the history match process.This new implemented method will give an overview of the simulation data quality workflow design and outline the development of a state of the art software package that guides engineers through the quality checking process as the first stage of simulation model construction.We have developed a workflow software package that covers most of the data required for building simulation models. The preparation and validation of data is conducted using tailored automated workflows that guide engineers through the quality control steps in a streamlined manner. At every step, specific data is reviewed and validated based on some well-developed quality check (QC) criteria. In case of any inconsistencies, the software issues relevant error and warning messages and recommends possible remedial solutions or actions.This tool eliminates tedious manual nonformal effort and results in high-quality simulation models checked and verified through formal and automated workflows, therefore. The new workflow/software reduces the checking process from weeks to days or hours and hence minimizes the overall time to perform history matching.

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Integrated Geological and Engineering Uncertainty Analysis Workflow, Lower Permian Carbonate Reservoir, Timan-Pechora Basin, Russia (Russian)

Cited by 3 publications

References 0 publications

Toward robust history matching of a giant carbonate gas‐condensate reservoir

Toward robust history matching of a giant carbonate gas‐condensate reservoir

Integrated Subsurface Uncertainty Study and Application - A Case Study of a Chalk Reservoir, Greater Ekofisk Area, North Sea

Automatic Well Completions and Reservoir Grid Data Quality Assurance for Reservoir Simulation Models

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