The aim of this study is to determine to what extent the quality of a history matched model is a good predictor of future production. The background is the common assumption that the better a model matches the production data is the better it is for forecasting, or, at the very least, it leads to an improved estimate of the uncertainty in future production. We demonstrate that the validity of this assumption depends on the length of the history match period and that of the forecasting period. It also depends on how heterogeneous the reservoir is.
The correlation between the quality of history match and quality of forecast depends on various factors. For the same level of heterogeneity one of the strongest factors is the water breakthrough time for the base and compared cases.
Broadly if both the base and compared case have water breakthrough before the end of the history match period then the forecasts are reasonable. However, there appears to be a very rapid transition from a reasonably good history match leading to a good forecast to a moderately good history match leading to a very poor forecast. If water breakthrough has not occurred there is a very poor correlation between the quality of the history match and the quality of the forecast. So, the traditional belief that a good history matched model will also produce a good forecast is not always true.
Polymer flooding is a proven EOR/IOR process for viscous and light oil reservoirs alike. However, it results in the formation of two shocks front that require simulation models with fine grid blocks to represent field scale fluid movement. Therefore, upscaling is required to transfer such fluid behavior to coarser models. However, most upscaling methods are designed for waterflood only, while upscaling techniques for polymer flood are rarely discussed in the literature.
In this paper, A new upscaling methodology specifically designed for polymer flooding is presented to address such impracticality. The methodology allows the average flow behavior to be captured, including the effects of small scale heterogeneity whilst compensating for the impact of increased numerical diffusion present in coarse grid models.
The method is based on the pore volume weighted method for relative permeability pseudoization first derived by
Extending the life of the Johnston field requires an ability to produce reliable forecasts of the effects of reservoir interventions. Reliable forecasts need an effective, robust and accurate history match. The goal of this paper is to evaluate the relative performance of three different global assisted history-matching algorithms. We describe the implementation of an integrated parameterization and optimization method, which was tested on the Brugge synthetic model (SPE benchmark case study), and the results based on the best selected method are applied to the Johnston gas field in the Southern North Sea.
There are two key components to assisted history matching: (i) choice of the parameterization, and (ii) selection and performance of the optimization algorithm. In this paper, three parameterization methods are tested (including use of gradients) on three global history-matching algorithms: Particle Swarm Optimization (PSO), Evolutionary Algorithm (EA) and Differential Evolution (DE). A combination of two different algorithms was also examined.
We assessed the algorithm efficiency based on the lowest achieved objective function and the time taken to converge to the lowest value; the quality of the parameterization was examined based on the lowest objective value, the best history match (the most geologically consistent models amongst the lowest objective function models) and the consistency of geological parameters used for the history match.
The results show that the effectiveness of each optimization algorithm is dependent on the parameterization method. When comparing parameterization methods, the Around the Median method seems to give the best results in terms of lowest misfit, and best history match when using the same history matching algorithm for the Brugge model example. When comparing across algorithms the DE method performs better than the rest. An iterative combination of algorithms is seen to be the best option and assists in a further minimization of the objective function. The effect of parameterization on match quality is also proved to be important. In some cases, an iterative process can be effective, where the history match is further improved by adding additional parameters or zoning existing parameters.
This paper stresses and illustrates the importance of the choice of parameterization methods, while many papers focus only on the performances of the minimization algorithm. It also combines gradient-based parameterization method with global optimization method.
During each of the three cases the initial transitions by the SA routine explore over a wide search space, including a nearly 50% of negative energy transitions (illustrated by the noisy portion of Figure 12, Figure 13 and Figure 14, for lower iteration values). These spikes die down at reduced values of control variable T as the Simulaed Annealing starts to optimise locally and finally converges to an optima. The optimised completion, for all the three cases, resulted in successful isolation of the portion of completed interval intersected by the high permeability streak. This is achieved by straddling the interval with packer and regulating the flow though an ICV. The optimal valve cross-section areas for the intervals that straddle the high permeability streak were found to be a few orders lower than the maximum. For the variable valve control case (Case-C), where the flow area can be changed a number of times during the course of the simulation, a few flow cross-section areas were found to fall out of trend (i.e., few orders different from the remaining values, for the same valve). This is characteristic of the SA routine since the control variables are randomly chosen. To overcome this limitation it is suggested that the optimal set of control parameters, in particular the valve flow cross-section areas, be refined using gradient based techniques like conjugate gradient method. This secondary use of gradient based techniques could also improve the value of objective function, since the logarithmic formulation used for generating random values of flow-cross-section area may overlook the global optima in the search space, while making transitions in multiples of 0.1.
In this paper we are continuing our previous works (SPE-143142 and WHOC11-353) to investigate the best development options for a major heavy oil reservoir within the GCC region. In the early stage of this work the most applicable EOR methods were selected, and several simulation runs were conducted to find the optimal injection scenarios and rank them based on the oil recovery factor (ORF). In this paper a comparative study and a sensitivity analysis of various operational conditions and reservoir parameters were conducted in order to (1) find the optimum conditions to achieve a high RF and (2) understand the effect of reservoir heterogeneity on the reservoir performance. The investigated operational parameters are the Steam injection rate, injection swapping time and the perforation location. The investigated reservoir parameters are oil viscosity, initial water saturation, porosity and permeability. In addition to investigating these reservoir parameters, the oil price sensitivity was investigated to evaluate the financial feasibility of the selected recovery methods within a historical and forecasted oil price range.
The preliminary results show that the RF is very sensitive to the oil viscosity value and the relation between them is a nonlinear relation. The Simulation results also indicate that the increase in the porosity and permeability accelerates performance; however, the opposite is not true for the initial water saturation value. From an economic perspective, production acceleration would improve overall project economics by mitigating the negative impact of discounting on the revenue stream due to the low oil price. Economically, all successive scenarios support a successful investment at the lowest (expected) oil price; in contrast, the continuous steam and hot-water flooding development options show a high economic risk after the second year, at all oil price scenarios.
Uncertainty and risk are two issues which usually highly considered when analyzing oil field development project. Risk analysis tries to predict the threats, opportunities and the impact of the uncertain input parameters on the project outcomes (Joshi, R. 2004). There are many uncertainties which can affect the success of any oil field development project as well affecting the rank of the optimum development strategies. These uncertainties include reservoir model, operational design parameters, oil price, OPEX, and CAPEX etc. In this paper, a comparative study and a sensitivity analysis of various operational conditions and reservoir parameters were conducted in order to (1) find the optimum conditions to achieve a high oil recovery and (2) understand the effect of reservoir heterogeneity on the reservoir performance. The investigated operational parameters are the steam injection rate, injection swapping time and perforation location. The investigated reservoir parameters are oil viscosity, initial water saturation, porosity and permeability. In addition to investigating these reservoir parameters, the oil price sensitivity was investigated to evaluate the economic feasibility of the selected recovery methods within a historical and forecasted oil price range.
In this paper, we investigate the sensitivity of reservoir properties and design parameters in sandstone heavy oil reservoir. To illustrate the potential of this sensitivity analysis, we discuss its application to our case study, reservoir X. However, the analysis presented here is general, and the sensitivity analysis strategy proposed could be applied readily to other suitable fields.
Roncaglia, Lucia (GNS Science) | Arnot, Malcolm (GNS Science) | Baur, Jan (GNS Science) | Fohrmann, Miko (GNS Science) | King, Peter (GNS Science) | Kroeger, Karsten Friedrich (GNS Science) | Ilg, Brad (GNS Science) | Strogen, Dominic (GNS Science) | Zhu, Hai (OMV New Zealand Ltd.) | Milner, Michael
This paper describes a multidisciplinary integrated workflow for mapping Late Cretaceous to Recent subsurface structure and stratigraphy, and modeling petroleum systems of the Taranaki Basin (74,209 km2), New Zealand. The basin-scale assessment of geology and fluid flow is aimed to improve previous, mostly local, studies. The size of the study area and integration over a nine-year timeframe of large datasets, multiple software and disciplines present technical challenges.
The workflow consists of the following six main tasks: data compilation, quality assessment and integration; structural and stratigraphic interpretation of seismic reflection data over a regional framework and local grids including assessment of timing and volumetrics of erosion; validation of the geometric and geological integrity of the structural framework through structural restoration; seismic attribute analysis and facies mapping to constrain the sedimentary facies distribution and the paleogeographic evolution of the basin; construction of 3D static models of stratigraphy, lithology distribution and faulting, as determined from the seismic and well interpretations; development of 4D dynamic models of basin deformation and petroleum generation and migration through time, to improve prediction of where as-yet undiscovered petroleum accumulations may be preserved.
Representative examples of data applications and results are presented for the hydrocarbon-producing Kupe area (4,155 km2). In Kupe, more than 200 fault planes and 20 laterally-continuous stratigraphic horizons are mapped, constrained by well data, and included in structurally-validated 3D framework models, which are populated with seismic attribute properties. The 4D models are created by integrating the results of all the steps of the workflow with source rock geochemical properties, heat-flow data from crustal-scale modeling, and rock properties for reservoir fairways.
This integrated workflow and associated data management and interpretation protocols have proved effective for developing a holistic 4D depiction of Taranaki Basin tectono-stratigraphy and petroleum systems. It provides a co-ordinated approach to interrogating large amounts of independent data, and the derivative models are the base for detailed petroleum exploration. Lessons learned may serve as guidelines for projects of similar scale.
Method, workflow, regional, modeling, facies, seismic, attribute, Kupe, Taranaki.
Use of sector models with fine grids that preserve the boundary conditions of the full field model has been of particular benefit to studying well coning behaviour for the different well geometries while allowing detail studies of the physics of flow and to optimize production rate by different well designs.
The objective of this project was to carry out simulation studies to investigate the pattern of gas coning and water encroachment for a bilateral well with the primary aim of
producing oil from a reservoir overlain by a large gas cap in Field A. High precision local refinement studies in the simulation model were undertaken to help place the wells
and optimize the completion design at the same time capturing the global field behaviour. This methodology was also used to properly simulate multilateral wells containing inflow control devices, allowing for pressure losses along the wellbore to be equalized and to minimize gas and water coning.
Prior to undertaking the simulation studies, several sensitivities were carried out to determine how other parameters such as boundary conditions and grid refinements could affect the output of near well bore models. By taking advantage of the time savings resulting from the generation of reduced fine grid models, several simulations were run to investigate the impact of different well configurations and operations due for instance to close/opening of valves or laterals.
The simulation studies resulted in the determination of the pattern of gas coning, water encroachment, optimum vertical placement of the oil lateral and the orientation of the gas lateral as they affect total recovery. The use of Inflow Control Device (ICD) was determined to be of benefit especially in controlling water and gas influx while providing a uniform production profile along the wellbore that delay gas and water coning and this is being incorporated now in the plan of development.