Hydrocarbon Field (Re-)Development as Markov Decision Process

Sieberer, Martin; Clemens, Torsten

doi:10.2118/206041-pa

Cited by 4 publications

(2 citation statements)

References 36 publications

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“…Each decision's conditional reward is determined by taking into account possible action combinations. When a decision-making process is multi-level, which happens when an event occurs in a series of levels, the DT Analysis approach is appropriate [40]. As a result, the DT Analysis approach is logically organised and appropriate for situations involving decision-making.…”

Section: Resultsmentioning

confidence: 99%

The Application of Decision Tree Classification Algorithm on Decision-Making for Upstream Business

Rahman,

Jamaludin,

Zainol

et al. 2023

IJACSA

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In today's rapidly advancing technological landscape and evolving business paradigms, the pursuit of insightful patterns and concealed knowledge beyond conventional big data becomes imperative. This pursuit serves a crucial role in aiding stakeholders, particularly in the realms of tactical decision-making and forecasting, with a particular focus on business strategy and risk management. Strategic and tactical decision-making holds the key to sustaining the longevity, profitability, and continuous enhancement of the oil and gas industry. Therefore, it is paramount to address this need by uncovering the most effective Decision Tree (DT) techniques for various challenges and identifying their practical applications in real-life scenarios. The integration of big data with Machine Learning (ML) stands as a pivotal approach to foster data-driven innovation within the oil and gas sector. This study aims to offer valuable insights and methodologies for efficient decisionmaking, catering to the diverse stakeholders within the oil and gas industry. It focuses on the exploration of optimal DT techniques for specific problems and their relevance in practical situations. By harnessing the potential of machine learning and collaborative efforts among research scientists, big data practitioners, data scientists, and analysts, the study strives to provide more precise and effective data. Furthermore, it is imperative to recognize that not all stakeholders are mathematicians. In project management, a holistic approach that considers humanistic perspectives, such as risk analysis, ethics, and empathy, is crucial. Ultimately, the output and findings of any system must be accessible, comprehensible, and interpretable by humans or human groups. The success of these insights lies not just in their mathematical precision but also in their ability to resonate with and guide human decision-makers. In this light, the study emphasizes the human element in data interpretation and decision-making, acknowledging that the system's output will require human interaction, analysis, and ethical considerations to be truly effective in driving positive outcomes in the industry.

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Section: Resultsmentioning

confidence: 99%

The Application of Decision Tree Classification Algorithm on Decision-Making for Upstream Business

Rahman,

Jamaludin,

Zainol

et al. 2023

IJACSA

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“…The final selection of the polymer needs to take all the points mentioned above into account. The selection of polymers for heterogeneous reservoirs requires dynamic simulation under uncertainty and integrated economic assessment to maximize the expected reward (Sieberer and Clemens [42]).…”

Section: Polymer Selectionmentioning

confidence: 99%

Selecting EOR Polymers through Combined Approaches—A Case for Flooding in a Heterogenous Reservoir

et al. 2022

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This work uses micromodel, core floods and Field-Flow Fractionation (FFF) evaluations to estimate the behaviour and key elements for selecting polymers to address heterogenous reservoirs. One of the approaches was to construct two-layered micromodels differing six times in permeability and based on the physical characteristics of a Bentheimer sandstone. Further, the impacts of injectivity and displacement efficiency of the chosen polymers were then assessed using single- and two-phase core tests. Moreover, FFF was also used to assess the polymers’ conformity, gyration radii, and molecular weight distribution. For the polymer selection for field application, we weighted on the good laboratory performance in terms of sweep efficiency improvement, injectivity, and propagation. Based on the results, polymer B (highest MWD) performed the poorest. Full spectrum MWD measurement using Field-Flow Fractionation is a key in understanding polymer behavior. Heterogenous micromodel evaluations provided consistent data to subsequent core flood evaluations and were in alignment with FFF indications. Single-phase core floods performed higher injection velocities (5 m/d) in combination of FFF showed that narrower MWD distribution polymers (polymers A and C) have less retention and better injectivity. Two-phase core floods performed at low, reservoir representative velocities (1 ft/d) showed that Polymer B could not be injected, with pressure response staying at high values even when chase brine is injected. Adsorption values for all tested polymers at these conditions were high, however highest were observed in the case of polymer B. Overall, for the polymer selection for field application, we weighted on the good laboratory performance in terms of sweep efficiency improvement, injectivity, polymer retention, and propagation; all accounted in this work.

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Polymer Selection for Sandstone Reservoirs Using Heterogeneous Micromodels, Field Flow Fractionation and Corefloods

Borovina

Reina

Clemens

et al. 2022

Day 1 Mon, April 25, 2022

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Incremental oil recovery due to polymer flooding results from acceleration of oil production along flow paths and improving sweep efficiency. To achieve favorable economics, polymers should have a high viscosifying power and low adsorption. However, in addition, incremental oil production from various rock qualities needs to be maximized. We developed a workflow using a layered micromodel, corefloods and Field-Flow Fractionation (FFF) to determine the Molecular Weight Distribution (MWD) for the selection of polymers addressing heterogeneous reservoirs. We have designed micromodels consisting of two layers with different permeabilities, one four times larger than the other. The micromodel structure is based on the characteristics of a real sandstone core, with the dimensions 6 cm × 2 cm. These micromodels were used as preliminary screening of the polymers incorporating heterogeneity effects. Subsequently, single- and two-phase core experiments were performed to determine injectivity effects and displacement efficiency of the selected polymers. In addition, FFF was used to measure the molecular weight distribution, gyration radii and conformance of the polymers. Based on the workflow a polymer was selected. All polymers were tested at target viscosity at 7 1/s shear rate. Micromodel experiments showed that tested polymers are leading to improved sweep efficiency of heterogeneous structure. The displacement efficiency within the higher permeable layer was similar for the investigated polymers whereas the oil recovery from the lower permeable layer showed differences. FFF revealed that the MWD's of the tested polymers were different. The MWD of one of the polymers showed a large number of larger molecules compared with the other polymers. This polymer did not lead to the highest oil recovery in the micromodel. Injectivity and propagation of the higher MW polymer in both single- and two-phase core-floods was falling behind the other polymers. Measurements of the MWD of the core effluent showed that for all tested polymers the larger molecules are initially retained more than the smaller molecules. The polymer with the smallest molecules and narrow MWD showed the best propagation characteristics in the core. Owing to the good performance of this polymer in terms of sweep efficiency improvement, injectivity, and propagation, this polymer was selected for a field application. Therefore, the novelty presented here can be summarised as follow: Heterogeneous micromodels were used to screen polymers for one-dimensional displacement efficiency and sweep efficiency effects Single- and two-phase core floods in combination with Field-Flow Fractionation revealed the impact of the molecular weight distribution (MWD) on polymer injectivity, propagation and retention Selection of polymers need to include MWD to find the most effective polymer Polymer selection needs to take near-wellbore and reservoir effects (micro- and sweep efficiency in heterogeneous reservoirs) into account

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Hydrocarbon Field (Re-)Development as Markov Decision Process

Cited by 4 publications

References 36 publications

The Application of Decision Tree Classification Algorithm on Decision-Making for Upstream Business

The Application of Decision Tree Classification Algorithm on Decision-Making for Upstream Business

Selecting EOR Polymers through Combined Approaches—A Case for Flooding in a Heterogenous Reservoir

Polymer Selection for Sandstone Reservoirs Using Heterogeneous Micromodels, Field Flow Fractionation and Corefloods

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