Mature Fields - Optimizing Waterflood Management Through DNA Based Diagnostics

Sawadogo, Jordan; Ursell, Luke K.; Reeve, Nicolai; Schlecht, Mathias

doi:10.2118/202912-ms

Cited by 4 publications

(1 citation statement)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to reservoir architecture, the dynamics of water flooding play a crucial role in determining production performance in oilfields. Water flooding, a widely adopted secondary recovery technique, involves injecting water into the reservoir to displace hydrocarbons and enhance recovery rates, , Understanding the water-cut changing pattern, which serves as a key indicator of production performance in water-flooded oilfields, is essential for effective reservoir management. Scholars have extensively studied water-cut dynamics using both theoretical and empirical approaches. , Theoretical methods, rooted in fundamental fluid mechanics principles, aim to model the complex multiphase flow behavior in porous media.…”

Section: Introductionmentioning

confidence: 99%

Refined Prediction Method for Production Performance of Deep-Water Turbidite Sandstone Oilfield: A Case Study of AKPO in Niger Delta Basin, West Africa

Kang,

Xiong,

Liu

et al. 2024

ACS Omega

View full text Add to dashboard Cite

Deep-water oilfields frequently employ large or superlarge well spacing, leading to significant production dynamics influenced by reservoir factors. Traditional methodologies often disregard these influences, resulting in poor accuracy. Therefore, an enhanced prediction methodology rooted in reservoir characteristics is proposed. This approach introduces the dynamic relative permeability law as a bridge, capturing macroscopic oil/water movement within the reservoir. For the first time, it integrates production dynamics with key controlling reservoir factors, encompassing reservoir architecture, injection-production connectivity, and reservoir heterogeneity. The results indicate that (1) In deep-water turbidite sandstone fields with ultralarge injector-producer well spacings, the distribution of oil−water movement is primarily influenced by reservoir connectivity and heterogeneity. The injection water sweeping ability coefficient can quantitatively describe the water flooding capacity, with a strong negative correlation between the injection water sweeping ability coefficient and interwell nonconnectivity coefficient and reservoir homogeneity coefficient. This suggests that better reservoir connectivity or weaker heterogeneity results in stronger water flooding capacity, leading to a wider range of water flooding under the same injection volume. (2) For regions with strong water flooding capacity (injection water sweeping ability coefficient 0.30−0.80), the water-free production period is the main production stage, with a focus on improving the planar flooding conditions. For regions with poor water flooding capacity (injection water sweeping ability coefficient 0.00−0.10), the middle and late water-cut periods are the main production stages, with a focus on improving interlayer dynamic differences in the later stages. For regions with moderate water flooding capacity (injection water sweeping ability coefficient 0.10−0.30), the initial focus should be on expanding planar flooding, followed by a focus on improving interlayer dynamic differences in the later stages. (3) The dynamic relative permeability law, capable of comprehensively portraying the reservoir's influence on macroscopic oil/water movement, emerges as a rational choice for production performance prediction in such contexts. Our method can improve the accuracy, compared with traditional method without geographical factors, from 45% to 90% during water-cut rising stage and 31% to 81% during production declining stage. The high prediction accuracy (90%) observed in the AKPO oilfields underscores the method's efficacy in directing on-site optimization and adjustments for the development of deep-water turbidite sandstone oilfields.

show abstract

Section: Introductionmentioning

confidence: 99%

Refined Prediction Method for Production Performance of Deep-Water Turbidite Sandstone Oilfield: A Case Study of AKPO in Niger Delta Basin, West Africa

Kang,

Xiong,

Liu

et al. 2024

ACS Omega

View full text Add to dashboard Cite

show abstract

Long-Term Microbial DNA-Based Monitoring of the Mature Sarukawa Oil Field in Japan

Kobayashi

Goto

Feng

et al. 2023

SPE Reservoir Evaluation &Amp; Engineering

View full text Add to dashboard Cite

Summary Microbial DNA-based monitoring is a promising tool for reservoir monitoring that has been used mainly for shale reservoir development. In this study, long-term microbial DNA-based monitoring was applied to the Sarukawa oil field, which has a complex reservoir structure with no practical simulation model available. Fluid samples were collected periodically from nine production wells and two injection wells from October 2019 to July 2021. DNA was extracted from the samples, and the microbial composition was analyzed by 16S ribosomal ribonucleic acid (rRNA) gene amplicon sequencing and real-time polymerase chain reaction (PCR). Based on similarities between the microbial profiles, the samples were classified into seven clusters that corresponded closely to the original fluid type (i.e., injection or production fluid) and specific environment (e.g., geological strata or compartments). A comparative analysis of the microbial profiles suggested possible well connectivity and water breakthrough. These results demonstrate that microbial DNA-based monitoring can provide useful information for optimizing production processes (e.g., waterflooding) in mature oil fields.

show abstract

Research on Production Profiling Interpretation Technology Based on Microbial DNA Sequencing Diagnostics of Unconventional Reservoirs

Yang

Wang

Qiang³

et al. 2022

Energies

View full text Add to dashboard Cite

Production profiling technology is an important method for monitoring the dynamics of oil and gas reservoirs which can effectively improve the efficiency of oil recovery. Production profiling is a technique in which a test instrument is lowered from the tubing to the bottom of the well to measure flow, temperature, pressure, and density in a multi-layer section of a producing well. Normal production profiling process needs to stop production, operate complex, consume long time and high cost. Furthermore, the profile cannot be continuously monitored for a long time. To address these limitations, this paper proposes a production profiling interpretation method based on reservoir primitive microbial DNA sequencing. The microbial stratigraphic baseline with high-resolution features is obtained by sampling and DNA sequencing of produced fluid and cuttings from different wells. Specifically, the random forest algorithm is preferred and improved by comparing the accuracy, precision, recall, F1-score, and running time of three clustering methods: Naïve-Bayes classifier, random forest classifier, and back-propagation classifier. Constructing PSO-random forest model is based on stratigraphic records and produced fluid bacteria features. The computational accuracy and efficiency of this method allows it to describe the production profile for each formation. Moreover, this test process does not need to stop production with simple operation and does not pollute the formation. Meanwhile, by sampling fluid production at different stages, it can achieve the purpose of long-term effective dynamic monitoring of the reservoir.

show abstract

Mature Fields - Optimizing Waterflood Management Through DNA Based Diagnostics

Cited by 4 publications

References 26 publications

Refined Prediction Method for Production Performance of Deep-Water Turbidite Sandstone Oilfield: A Case Study of AKPO in Niger Delta Basin, West Africa

Refined Prediction Method for Production Performance of Deep-Water Turbidite Sandstone Oilfield: A Case Study of AKPO in Niger Delta Basin, West Africa

Long-Term Microbial DNA-Based Monitoring of the Mature Sarukawa Oil Field in Japan

Research on Production Profiling Interpretation Technology Based on Microbial DNA Sequencing Diagnostics of Unconventional Reservoirs

Contact Info

Product

Resources

About