Enhancing Field Management in Siberia by Quantifying Production Uncertainties (Russian)

This paper demonstrates the multivariate approach as a tool for the management of initial data uncertainties in 3D reservoir simulation processes. The multivariate approach helps to address several problems, including optimizing the development scenario, determining the well type, and calculating the optimal horizontal well completion system.The method for determining the optimal development scenarios includes performing multiple forecast runs on simulation models with variations of initial data (such as permeability and water/oil contact) for various development scenarios (including well spacing and development plan). Then, the data are systematized, and a statistical analysis is performed with the calculation of economic indicators. The distributions of technical and economic development parameters are built from the results of these processes. The optimal development scenario is selected directly by selecting the realization with the maximum probability of occurrence from the most economically successful realizations. In other words, a development scenario is considered optimal if it has maximum probability of occurrence in the data set and maximum economic indicators (net present value (NPV) and profitability index (PI)).The paper uses two case studies to illustrate the multivariate approach for determining the optimal development scenarios by considering the initial data uncertainties.For gas field A (eastern Caspian, lower Jurassic terrigenous deposits), the task of determining the optimal well type and spacing of the new wells was addressed by using multivariate reservoir simulation. The data uncertainty is attributable to a core test result error in the permeability determination and to a lack of data for the gas/water contact depth in accordance with the well testing and production testing results. A total of 10,000 simulations of the multivariate reservoir and economic model were run to determine the optimal well type and well spacing. In addition, probabilistic values of the development technical and economic indicators P10, P50, and P90 were determined. The results of the calculation enabled the optimal development parameters to be selected and the effect of the initial data uncertainties on the final technical and economic indicators of the field development to be evaluated.The length of horizontal wells, hydraulic fracture spacing, and optimal well spacing were selected based on the multivariate approach for oilfield B (western Siberian oil and gas province, upper Jurassic). For this purpose, 100,000 iterations of the development scenarios forecast were calculated based on the multivariate simulation model. Based on the analysis of the calculations and economic model, the optimal length of the horizontal section and fracture spacing were selected and justified, enabling the optimal design and completion system for horizontal wells, as well as risk mitigation measures, to be selected.

Section: The Concept Of Multivariate Approach In 3d Reservoir Simulationmentioning

confidence: 99%

Management of Initial Data Uncertainties in 3D Reservoir Simulation

Sadykov

Mikhaylov

2015

Integrated Approach to Hydraulic Fracturing of Achimov Formation in Western Siberia

Marino

Butula²,

Mauth³

et al. 2010

Since its introduction in the petroleum industry, hydraulic fracturing has been one of the primary engineering tools for reservoir stimulation and well productivity enhancement. Creating a conductive channel in a reservoir to increase hydrocarbon recovery is a complex operation involving a variety of aspects including geology, petrophysics, production engineering, geomechanics, and fluid mechanics. Designing a treatment to achieve the desired fracture dimensions and orientation is intimately connected with rock mechanics. A mechanical earth model was built in support of a hydraulic fracturing treatment performed on the Achimov formation in the West Salym oil field, Western Siberia, operated by Salym Petroleum Development. This deep and laminated formation is suspected to lie above water-bearing layers, which makes its stimulation technically challenging. The study involved various petrotechnical skills. First, the modeling of the rock mechanical properties required standard wellbore measurements and acoustic logging. The calibration of the minimum horizontal stress profile was achieved by post-closure analysis of the minifracture performed before the main fracturing treatment, and by interpretation of temperature logs. Then, the fracture growth was simulated using hydraulic fracturing software. Analysis of the main treatment was augmented with bottomhole pressure (BHP) recorded by a memory gauge installed in the wellbore. The simulated BHP could thus be compared with and matched to the measured BHP in order to calibrate the fracture model. Finally, fracture mapping by the differential cased hole sonic anisotropy technique allowed for verification of the obtained geometry and the suspected orientation. This unique combination of measurements and analyses enabled a thorough evaluation of fracture parameters that can be extended to neighboring wells. Geomechanics modeling has proven to be an invaluable tool in the struggle to understand and predict fracture growth, as well as to optimize fracturing treatments. The accuracy of the preliminary fracture design helped to define the best solution very early. By employing the described approach, remarkable knowledge was gained on the local state of stress, which will have a positive impact on reservoir management and field development planning.

Using Crosswell Data To Enhance History Matching

Ravanelli

Hoteit

2014

One of the most challenging tasks in the oil industry is the production of reliable reservoir forecast models. Due to different sources of uncertainties in the numerical models and inputs, reservoir simulations are often only crude approximations of the reality. This problem is mitigated by conditioning the model with data through data assimilation, a process known in the oil industry as history matching. Several recent advances are being used to improve history matching reliability, notably the use of time-lapse data and advanced data assimilation techniques. One of the most promising data assimilation techniques employed in the industry is the ensemble Kalman filter (EnKF) because of its ability to deal with non-linear models at reasonable computational cost. In this paper we study the use of crosswell seismic data as an alternative to 4D seismic surveys in areas where it is not possible to re-shoot seismic. A synthetic reservoir model is used in a history matching study designed better estimate porosity and permeability distributions and improve the quality of the model to predict future field performance.This study is divided in three parts: First, the use of production data only is evaluated (baseline for benchmark). Second, the benefits of using production and 4D seismic data are assessed. Finally, a new conceptual idea is proposed to obtain timelapse information for history matching. The use of crosswell time-lapse seismic tomography to map velocities in the interwell region is demonstrated as a potential tool to ensure survey reproducibility and low acquisition cost when compared with fullscale surface surveys. Our numerical simulations show that the proposed method provides promising history matching results leading to similar estimation error reductions when compared with conventional history matched surface seismic data.