From Test Tube to Value Generator: Effective Use of Experimental Design for Uncertainty Analysis and Development Concept Optimisation

Kloosterman, H. J.; Herring, Todd; Tull, Simon; Lee, Jan-Willem van der

doi:10.2118/106893-ms

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…Various authors have used DoE approach to study the effect of subsurface uncertainties in different types of fields such as offshore heavy oil field (Vanegas et al, 2005), gas condensate field (Abdul-Latif et al, 2017), onshore light oil field (Kloosterman et al, 2007). Peake et al (Figure 12).…”

Section: Application Of Design Of Experiments/rsm In Reservoir Simulamentioning

confidence: 99%

Application of Design of Experiments for Well Pattern Optimization in Umiat Oil Field: A Natural Petroleum Reserve of Alaska Case Study

Gurav

Dandekar

Patil

et al. 2020

Day 2 Wed, October 30, 2019

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Umiat field, located in Alaska North Slope (ANS) poses unique development challenges because of its remote location and permafrost within the reservoir. This hinders the field development, and further leads to a potential low expected oil recovery. The objective of this work is to assess various possible well patterns of the Umiat field development, and perform a detailed parametric study to maximize oil recovery and minimize well costs using statistical methods. Design of Experiments (DoE) is implemented to design simulation runs for characterizing system behavior using the effect of certain critical parameters, such as well type, horizontal well length, well pattern geometry, and injection/production constraints on oil recovery. After carrying out simulation runs using a commercially available simulation software, well cost is estimated for each simulation case. Response Surface Methodology (RSM) is used for optimization of well pattern parameters. The parameters, their interactions and response are modeled into a mathematical equation to maximize oil recovery and minimize well cost. Economics plays a key role in deciding the best well pattern for any field during the field development phase. Hence, while solving the optimization problem, well costs have been incorporated in the analysis. Thus, based on the results of the study performed on selected parameters, using interdependence of the above mentioned methodologies, optimum combinations of variables for maximizing oil recovery and minimizing well cost will be obtained. Additionally, reservoir level optimization assists in providing a much needed platform for solving the integrated production optimization problem involving parameters relevant at different levels, such as reservoir, wells and field. As a result, this optimum well pattern methodology will help ensure optimum oil recovery in the otherwise economically unattractive field, and can provide significant insights into developing the field more efficiently. Computational algorithms are gaining popularity for solving optimization problems, as opposed to manual simulations. DoE is effective, simple to use and saves computational time, when compared to algorithms. Although DoE has been used widely in the oil industry, its application in domains like well pattern optimization is novel. This paper presents a case study for the application of DoE and RSM to well optimization in a real existing field, considering all possible scenarios and variables.

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Section: Application Of Design Of Experiments/rsm In Reservoir Simulamentioning

confidence: 99%

Application of Design of Experiments for Well Pattern Optimization in Umiat Oil Field: A Natural Petroleum Reserve of Alaska Case Study

Gurav

Dandekar

Patil

et al. 2020

Day 2 Wed, October 30, 2019

View full text Add to dashboard Cite

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Experimental Design in reservoir simulation: an integrated solution for uncertainty analysis, a case study

Moeinikia

Alizadeh

2012

J Petrol Explor Prod Technol

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Quantification of uncertain parameters in oil reservoirs is one of the major issues of concern. In underdeveloped reservoirs, there are many uncertain parameters affecting production forecast which plays a main role in reservoir management and decision making in development plan. To study the effect of uncertain parameters on the behavior of a reservoir and to forecast the probabilistic production of the reservoir, the simulator has to be run too many times with different entries for uncertain parameters. To avoid this heavy and timeconsuming process, Experimental Design methodology is used which chooses the values of uncertain parameters from their ranges in a way that the total uncertainty in the system is captured with the least number of simulator runs. In this study, Experimental Design methodology is used to observe the effect of uncertain parameters on the production of an underdeveloped oil reservoir, which is subjected to immiscible gas injection method, and to estimate the probabilistic production of the reservoir; therefore, the proper and unbiased decisions for oil reservoir development can be made. Experimental Design methodology, as a powerful and trusted method, makes it possible to choose simulator runs so as to obtain accurate probabilistic production diagrams using the least number of runs as well as to study the impact of uncertain parameters on the oil reservoir production profile, quickly.

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Seeking the Ultimate Field Development Using the Well Maturity Index

Kloosterman¹,

Herring²,

Tull³

et al. 2008

All Days

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A case study is presented from an oil field in the Sultanate of Oman, operated by Petroleum Development Oman. To date the field has seen limited production under natural depletion (~1% of STOIIP produced). Most of the oil is located in 20–25 m thick oil rims with large gas caps in the reservoirs of the Gharif and Al Khlata formations. A Field Study was kicked off in PDO in 2004, triggered by the results of recent appraisal wells and has substantiated significant additional field potential. This paper extends previous work [Ref 1] in which we set out the use of Experimental Design for subsurface uncertainties analysis and development options evaluation for an oil field in the Sultanate of Oman. Here, we demonstrate for the first time how the multi-scenario ED modeling results can be taken one step further in Field Development optimisation. We introduce the concept of "Well Maturity Index" which quantifies the impact of subsurface uncertainties on EUR for each well in the selected development. The Well Maturity Index was used to guide decisions on the phasing of development and appraisal drilling and to help formulate a data acquisition programme for the field. This approach has resulted in an auditable and quantified decision-based plan for maximizing NPV and minimising risk, and adds significant value to the development planning process. This work also provides a natural stepping stone for a quantifiable Value of Information analysis, and scenario planning based on appraisal outcomes. The methodology used is general and should find application in many field development studies.. Introduction The Case Study field is located in onshore North Oman and is operated by Petroleum Development Oman. The relatively light oil is located in stacked oil rims beneath large gas caps in four different reservoirs (AK, LG, MG and UG). The field is associated with a mainly dip-closed, low relief faulted anticline, with its crest at a depth of 3000 m. Intervening shales and tight limestones act as intra-reservoir seals, and the UG, MG and LG/AK formations have separate fluid contacts. To date the field has seen limited production under natural depletion with three phase flow to remote processing facilities. A schematic of the field is given in Figure 1. A Field Development Plan (FDP) was derived after an extensive multi-scenario modeling approach using Experimental Design [Ref 1], followed by deterministic optimisation and by testing of the development against subsurface uncertainty. Key elements of the FDP are:Initial drilling to fill existing and committed facilities with low GOR oil by developing the AK oil rim with horizontal wells, coupled with appraisal of the overlying LG MG and UG reservoirs.Installation of full field facilities. Gas separation and compression with gas and oil/water routed to dedicated processing facilities. The increased capacity to be filled with production from potentially higher GOR LG and UG reservoirs.Final gas cap blow down will be carried out at the end of economic oil production. The multi-scenario ED results have also created a wealth of useful data, that can be further explored. A more detailed quantification of the impact of subsurface uncertainties can be pursued for the final development, on a well by well basis. This paper describes how this has further refined the phasing of development and appraisal drilling and how this has tailored the data acquisition programme to be more specific to each of the wells. Also, ranges for key surface facility design parameters were defined and were used for further optimisation the design specifications. Experimental Design Results Experimental Design is a mathematical technique which aims at representative sampling of the full parameter space with a relatively small number of parameter combinations. It is now widely recognized in the oil industry that ED provides a robust and time efficient way of handling multi-factorial problems such as volumetric calculations, history matching and development screening [Ref 1- 8].

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From Test Tube to Value Generator: Effective Use of Experimental Design for Uncertainty Analysis and Development Concept Optimisation

Cited by 3 publications

References 7 publications

Application of Design of Experiments for Well Pattern Optimization in Umiat Oil Field: A Natural Petroleum Reserve of Alaska Case Study

Application of Design of Experiments for Well Pattern Optimization in Umiat Oil Field: A Natural Petroleum Reserve of Alaska Case Study

Experimental Design in reservoir simulation: an integrated solution for uncertainty analysis, a case study

Seeking the Ultimate Field Development Using the Well Maturity Index

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