Successful Completion Operations on Ravenspurn North Development

Prise, G.J.; Stewart, Dave; Bird, Tim; Holland, Brian; Wilson, W. W.

doi:10.2118/26744-ms

Cited by 5 publications

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“…Despite their production potential, shale gas reservoirs are often highly heterogeneous [10,11] and have poor petrophysical properties [12][13][14]. Parameters such as shale thermal maturity, organic matter content, net thickness, burial depth, recoverable area, gas content, and Young's modulus are used to describe shale gas reservoirs [15].…”

Section: Introductionmentioning

confidence: 99%

Reservoir Characteristics of the Lower Silurian Longmaxi Shale in Zhaotong Region, Southern China

et al. 2020

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The lower Silurian Longmaxi Formation hosts a highly productive shale gas play in the Zhaotong region of southern China. According to core observation, X-ray diffraction analyses, and scanning electron microscopy (SEM) observations, the shale comprises primarily quartz, carbonate minerals, and clay minerals, with minor amounts of plagioclase, K-feldspar, and pyrite. The clay mineral content ranges from 15.0% to 46.1%, with an average of 29.3% in the Zhaotong region. Organic geochemical analyses show that the Longmaxi Formation has good potential for shale gas resources by calculating total organic carbon, vitrinite reflectance, and gas content. Scanning electron microscope images demonstrate that reservoir pore types in the Longmaxi shale include organic pores, interparticle pores, intercrystalline pores, intraparticle pores, and fractures. Reservoir distribution is controlled by lithofacies, mineral composition, and geochemical factors. In addition, we investigated the relationships between reservoir parameters and production from 15 individual wells in the Zhaotong region by correlation coefficients. As a result, the brittleness index, total organic carbon (TOC), porosity, and gas content were used to define high-quality reservoirs in the Longmaxi shale. Based on these criteria, we mapped the thickness and distribution of high-quality reservoirs in the Longmaxi Formation and selected highlighted several key sites for future exploration and development.

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Section: Introductionmentioning

confidence: 99%

Reservoir Characteristics of the Lower Silurian Longmaxi Shale in Zhaotong Region, Southern China

et al. 2020

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An Unsupervised Machine Learning Based Double Sweet Spots Classification and Evaluation Method for Tight Reservoirs

Deng¹,

Wang

Su³

et al. 2023

Journal of Energy Resources Technology

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With the increasing exploration and development of tight sandstone gas reservoirs, it is of utmost importance to clarify the characteristics of “sweet spots” within tight gas reservoirs. Considering the complex lithology of tight gas reservoirs, fast phase transformations of sedimentary facies, and vital diagenetic transformation, there is a low success rate of reservoir prediction in the lateral direction, and heterogeneity evaluation is challenging. Establishing a convenient standard for reservoir interpretation in the early stages of development is complex, making designing hydraulic fracturing in the later phases a challenge. In this paper, we propose a detailed study of the engineering and geological double sweet spots (DSS) analysis system and the optimization of sweet spot parameters using the independent weight coefficient method. K-means++ algorithm and Gaussian mixture gradient algorithm unsupervised machine learning algorithms are used to determine the classification standard of general reservoirs and high-quality sweet spot reservoirs in the lower 1 layer of He-8 in the x block of the Sulige gas field. This application of the field example illustrates that the proposed double sweet spot classification and evaluation method can be applied to locate the reservoir's sweet spot accurately.

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Unlocking the Future for a Mature Field: Surveillance and Complex Wellwork Combine to Extend Field Life

Dunning

Davies

Keatinge

et al. 2011

SPE Offshore Europe Oil and Gas Conference and Exhibition

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Ravenspurn North is a mature gas field forming part of BP's UKCS portfolio. The field commenced production in 1990 through 42 wells and 3 platforms but by 2006 half of the wells had ceased to flow. Surface pressures suggested limited remaining gas and, with declining production, the field was at risk of abandonment.A surveillance campaign carried out in 2006 suggested a common failure mode for many wells, which postulated that large amounts of proppant had accumulated in the wellbore. Pressures measured downhole above the proppant fill supported a significant increase of the remaining gas potential.A project to rejuvenate this field was initiated in 2007. The key to this project was cleaning out and reinstating non-flowing wells across the field. This would require pushing the boundaries of cleanout techniques and delivering a number of industry firsts, all on normally unmanned installations with complex logistical challenges. Additionally, each individual well intervention would be economically marginal on a standalone basis -the project had to place these interventions into a wider business context before building the case to justify the investment needed to resolve the many challenges presented. This paper details the journey to maximise the potential of the mature Ravenspurn North field. It starts with the acquisition of surveillance in 2006 and covers how the business case was built to justify one of BP's most complex well intervention programmes in the North Sea (concentric coiled tubing vacuum technology on a small unmanned platform). It culminates in the successful execution of the first phase of wells in 2010.With the first phase of the Ravenspurn North rejuvenation complete, this paper reflects on the lessons learned along the way and identifies the key activities which have contributed to delivering a longer, brighter future for this field.

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Successful Completion Operations on Ravenspurn North Development

Cited by 5 publications

References 0 publications

Reservoir Characteristics of the Lower Silurian Longmaxi Shale in Zhaotong Region, Southern China

Reservoir Characteristics of the Lower Silurian Longmaxi Shale in Zhaotong Region, Southern China

An Unsupervised Machine Learning Based Double Sweet Spots Classification and Evaluation Method for Tight Reservoirs

Unlocking the Future for a Mature Field: Surveillance and Complex Wellwork Combine to Extend Field Life

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