Geological modeling of combined incised channel system in deep-water gravity flow sedimentation: The case of OML130 in Niger delta basin, West Africa

Bu, Fanqing; Zhang, Xu

doi:10.1016/j.jafrearsci.2019.103704

Cited by 2 publications

(5 citation statements)

References 15 publications

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“…Drawing from prior research findings concerning deep-water turbidite sandstone reservoir architecture, it is evident that reservoir architecture within deep-water turbidite sandstone oilfields can be categorized into three distinctive modes. , Notably, each of these different reservoir architecture modes corresponds to distinct production dynamics patterns, as supported by extensive statistical analysis of actual production data. In essence, the reservoir architecture modes serve as a foundational basis for making preliminary assessments of the production dynamics of target wells. “Mode I” signifies the same-layer connection.…”

Section: Refined Prediction Methodsmentioning

confidence: 89%

“…11−15 Researchers have devoted significant efforts to understanding and characterizing these reservoir architectures, drawing on a combination of seismic data, well data, and production performance data. 16−18 Techniques such as optimizing P/S wave velocity ratios and seismic attributes have been employed to characterize the connectivity of channel sands qualitatively and quantitatively zones, 19 facilitating the delineation of sand superposition zones and the identification of distinct configuration styles. 20−23 In addition to reservoir architecture, the dynamics of water flooding play a crucial role in determining production performance in oilfields.…”

Section: Introductionmentioning

confidence: 99%

“…The unique geological characteristics of deep-water turbidite sandstone reservoirs further complicate the development process. − These reservoirs are formed through the interplay of hydrodynamic forces and successive evolutionary stages, resulting in complex spatial arrangements of multistage channel sands. The variability in the relationships between these channel sand overlays gives rise to diverse reservoir architectures, even within the same oilfield. − Researchers have devoted significant efforts to understanding and characterizing these reservoir architectures, drawing on a combination of seismic data, well data, and production performance data. − Techniques such as optimizing P/S wave velocity ratios and seismic attributes have been employed to characterize the connectivity of channel sands qualitatively and quantitatively zones, facilitating the delineation of sand superposition zones and the identification of distinct configuration styles. − …”

Section: Introductionmentioning

confidence: 99%

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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

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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.

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Section: Refined Prediction Methodsmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

“…Fit the actual production data of 13 producing wells with Equation (15) to determine the parameter d 1 , d 2 values of each mode in Akpo oilfields (Table 5). According to the prediction result of water-cut, the liquid production rate can be forecasted with Equation (15). Production wells can be divided into three types according to TVD and well type in Akpo oilfields.…”

Section: Application and Discussionmentioning

confidence: 99%

“…The P/S wave velocity ratio, seismic attributes, and production performance data were optimized, and the targeted qualitative and quantitative characterizations of the connected area between channel sandbodies by demarcating the sandbody superposition area were realized. And a deep-water turbidite sandstone reservoir structure can be divided into three modes including the same-layer connection, the composite connection, and the interlayer connection [14,15].…”

Section: Introductionmentioning

confidence: 99%

A Prediction Method for Flow-Stop Time in Deep-Water Volatile Oilfields: A Case Study of Akpo Oilfield in Niger Delta Basin

Kang

Liu

Li³

et al. 2021

Geofluids

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Due to the difference in oil and water density, the wellhead pressure continues to decrease with water-cut rising in deep-water volatile oilfields. Once it is close to the lower limit, the production well will stop flowing. This phenomenon seriously affects the production and recoverable reserves. By taking the dynamic relative permeability which can reflect the macroscopic movement of oil and water in the reservoir as an intermediate bridge, production performance has been combined with dominant reservoir factors, including reservoir structure, reservoir connectivity, and heterogeneity. By the statistical analysis of actual data, this paper clarified the quantitative relationships between dominant reservoir factors and production performance and established the refined prediction methods for production dynamics including water-cut and liquid production rate. A prediction method for the wellhead pressure was further established, and the flow-stop time of single well can be accurately predicted. The results can be used in annual production forecast and recoverable reserve evaluation. This method had been successfully applied in Akpo oilfields in the Niger Basin. The results show that the production dynamics are significantly affected by reservoir factors in deep-water turbidite sandstone reservoir and the prediction method considering reservoir factors will be much more applicable. In deep-water volatile oilfields, the flow-stop risk of the production well in middle and high water-cut stages is very great and is mainly affected by the water-cut and liquid production rate. Judging from the application effect of Akpo oilfields, this method has high prediction accuracy and can be used to guide optimization and adjustment in deep-water oilfields.

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Geological modeling of combined incised channel system in deep-water gravity flow sedimentation: The case of OML130 in Niger delta basin, West Africa

Cited by 2 publications

References 15 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

A Prediction Method for Flow-Stop Time in Deep-Water Volatile Oilfields: A Case Study of Akpo Oilfield in Niger Delta Basin

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