Database technology for deep marine clastic characterisation: upscaling for impact
Lead Research Organisation:
University of Leeds
Department Name: School of Earth and Environment
Abstract
The geological characteristics of subsurface sedimentary rocks control the amount of oil, gas and/or water present within them (as hydrocarbon reservoirs or aquifers), and how such fluids will flow. Petroleum geologists build three-dimensional numerical models to assess the likely amount and flow rates of oil and gas and optimum well locations. These models ultimately determine whether hydrocarbon production is successful. (Hydrogeologists develop corresponding geological models to predict water yield or contaminant transport, in order to inform aquifer exploitation and clean-up; such models are also required to assess the feasibility of programmes of underground carbon capture and storage). When these models are built, geologists have available only limited direct subsurface data with which to constrain the type and geometry of subsurface geological bodies and thus their fluid-flow characteristics. To complement the sparse direct data, exposed outcrops of similar types of rocks, or modern sedimentary environments where comparable sediments are deposited, can be used as 'analogues' to hydrocarbon reservoirs or aquifers. These analogues provide proxy information regarding geological features that determine reservoir or aquifer heterogeneity. Within a reservoir or aquifer, these geological heterogeneities exert a primary control on well connectivity, flow rates, and behaviour to production or clean-up strategies, thereby dictating how much oil or gas is likely to be produced from a reservoir, or whether contaminants are successfully removed from the groundwater. Quantitative analogue data on these geological heterogeneities are required as input for constraining geological models of the subsurface. The derivation of this type of data from databases is an integral part of subsurface modelling workflows, but current approaches are inadequate because of the limited volume and quality of data stored in existing databases, and their current poor integration with existing modelling tools.
The Leeds IP consists of three different relational databases that contain analogue data about types of rock volumes that constitute the building blocks of geological models of reservoirs or aquifers; each database relates to a particular geological setting. All data are stored in a format that allows quantitative output to be produced, in forms that can be fed into all the common numerical methods used to build models of subsurface heterogeneity. The technology of the IP surpasses similar databases in terms of data quality and format. The fact that a fuller characterisation of sedimentary heterogeneity is achieved by these databases enables the derivation of the output required by existing modelling algorithms: this makes the IP unique in its class.
However, the current value of the combined IP is limited by the relative underdevelopment of the Deep Marine Clastic database, and its current inability to integrate fully with software platforms employed to generate and manage geological models of the subsurface, such as Schlumberger's Petrel. Thus, the up-scaling of this database and the development of an interface for the optimal integration of the Deep Marine Clastic database with Petrel are key requirements for making this IP marketable, and leveraging the full value of the integrated databases.
Upon successful development, the IP will enable easy access and application of large volumes of high-quality data in the area of Deep Marine Clastics, in parallel with that from other environments. This technology will aid geologists and engineers in the hydrocarbon and water-management industries in the generation of geologically sensible reservoir and aquifer models.
The project will be undertaken by Marco Patacci, currently a PDRA at Leeds, and supervised by Bill McCaffrey, who is a sedimentologist and director of the Turbidites Research Group, and Nigel Mountney (sedimentologist).
The Leeds IP consists of three different relational databases that contain analogue data about types of rock volumes that constitute the building blocks of geological models of reservoirs or aquifers; each database relates to a particular geological setting. All data are stored in a format that allows quantitative output to be produced, in forms that can be fed into all the common numerical methods used to build models of subsurface heterogeneity. The technology of the IP surpasses similar databases in terms of data quality and format. The fact that a fuller characterisation of sedimentary heterogeneity is achieved by these databases enables the derivation of the output required by existing modelling algorithms: this makes the IP unique in its class.
However, the current value of the combined IP is limited by the relative underdevelopment of the Deep Marine Clastic database, and its current inability to integrate fully with software platforms employed to generate and manage geological models of the subsurface, such as Schlumberger's Petrel. Thus, the up-scaling of this database and the development of an interface for the optimal integration of the Deep Marine Clastic database with Petrel are key requirements for making this IP marketable, and leveraging the full value of the integrated databases.
Upon successful development, the IP will enable easy access and application of large volumes of high-quality data in the area of Deep Marine Clastics, in parallel with that from other environments. This technology will aid geologists and engineers in the hydrocarbon and water-management industries in the generation of geologically sensible reservoir and aquifer models.
The project will be undertaken by Marco Patacci, currently a PDRA at Leeds, and supervised by Bill McCaffrey, who is a sedimentologist and director of the Turbidites Research Group, and Nigel Mountney (sedimentologist).
Planned Impact
The project has the potential to generate impact of economic, societal and academic nature.
The project execution will favour commercial uptake of the IP specific to the field of Deep Marine Clastics, and will further enable the value of a modelling approach that can be integrated across the full suite of clastic environments "from source to sink" i.e., across continental, shallow- and deep-marine settings, to be realised. Currently, the value of the IP is restricted by its unproven integration with industry workflows and the relatively small scale of the current database. Demonstration of technical feasibility for data integration into industry modelling workflows, and of the critical mass of data in the database will attract potential commercial partners. If successfully commercialised, the IP will have prompted a more widespread adoption of the associated technology in industry best-practice. It is foreseeable that this route will maximise the economic, societal and academic impact of the IP.
Industry uptake of the technology will result in the improvement of both the efficiency and end-results of the workflows applied to the subsurface geological modelling of hydrocarbon reservoirs and aquifers. These improvements will likely be reflected in the decision making for which these models are built. Crucially, better informed decision making regarding exploitation of natural resources has both societal and economic impact. The generation of more realistic subsurface models enabled by the technology will have an impact on the efficiency of hydrocarbon production, enhancing production volumes and rates and lowering costs. The high level of sophistication in the construction of subsurface geological models permitted by the IP is particularly required in application to hydrocarbon fields that are nearing depletion (e.g. many oil fields in the North Sea), and in the modelling effort required around the relatively immature use of such fields as CO2 sequestration reservoirs. The same IP would be applied in a similar way to create geological models of aquifers, which are routinely used to simulate groundwater yield and contaminant transport. The impact of the proposed IP on the modelling practice in the hydrogeology industry could be significant. Firstly because of a tendency to overlook geological realism when building aquifer models, in relation to the comparatively limited economic implications of the decisions taken in the water-management industry on the basis of these models, and secondly because of the potentially wider scale of the ultimate beneficiaries.
Commercialisation of the IP will generate academic impact in a number of ways. Impact will be generated by demonstrating how fundamental-research outcomes are progressively translated into viable commercial applications; successful commercialisation will make this project serve as an impact case study. Popularization of the IP will promote engagement with academic researchers interested in the technology, widening possibilities for collaborative work, which would ultimately result in publishable output. Commercialisation of the IP will create opportunity for further collaboration and knowledge-transfer with industry, and will serve as an advertisement for support of academic work through industrial sponsorships.
The project execution will favour commercial uptake of the IP specific to the field of Deep Marine Clastics, and will further enable the value of a modelling approach that can be integrated across the full suite of clastic environments "from source to sink" i.e., across continental, shallow- and deep-marine settings, to be realised. Currently, the value of the IP is restricted by its unproven integration with industry workflows and the relatively small scale of the current database. Demonstration of technical feasibility for data integration into industry modelling workflows, and of the critical mass of data in the database will attract potential commercial partners. If successfully commercialised, the IP will have prompted a more widespread adoption of the associated technology in industry best-practice. It is foreseeable that this route will maximise the economic, societal and academic impact of the IP.
Industry uptake of the technology will result in the improvement of both the efficiency and end-results of the workflows applied to the subsurface geological modelling of hydrocarbon reservoirs and aquifers. These improvements will likely be reflected in the decision making for which these models are built. Crucially, better informed decision making regarding exploitation of natural resources has both societal and economic impact. The generation of more realistic subsurface models enabled by the technology will have an impact on the efficiency of hydrocarbon production, enhancing production volumes and rates and lowering costs. The high level of sophistication in the construction of subsurface geological models permitted by the IP is particularly required in application to hydrocarbon fields that are nearing depletion (e.g. many oil fields in the North Sea), and in the modelling effort required around the relatively immature use of such fields as CO2 sequestration reservoirs. The same IP would be applied in a similar way to create geological models of aquifers, which are routinely used to simulate groundwater yield and contaminant transport. The impact of the proposed IP on the modelling practice in the hydrogeology industry could be significant. Firstly because of a tendency to overlook geological realism when building aquifer models, in relation to the comparatively limited economic implications of the decisions taken in the water-management industry on the basis of these models, and secondly because of the potentially wider scale of the ultimate beneficiaries.
Commercialisation of the IP will generate academic impact in a number of ways. Impact will be generated by demonstrating how fundamental-research outcomes are progressively translated into viable commercial applications; successful commercialisation will make this project serve as an impact case study. Popularization of the IP will promote engagement with academic researchers interested in the technology, widening possibilities for collaborative work, which would ultimately result in publishable output. Commercialisation of the IP will create opportunity for further collaboration and knowledge-transfer with industry, and will serve as an advertisement for support of academic work through industrial sponsorships.
Publications
Bührig L
(2022)
Tectonic Influence on the Geomorphology of Submarine Canyons: Implications for Deep-Water Sedimentary Systems
in Frontiers in Earth Science
Bührig L
(2022)
A global analysis of controls on submarine-canyon geomorphology
in Earth-Science Reviews
Cullis S
(2019)
A database solution for the quantitative characterisation and comparison of deep-marine siliciclastic depositional systems
in Marine and Petroleum Geology
Cullis S
(2018)
Hierarchical classifications of the sedimentary architecture of deep-marine depositional systems
in Earth-Science Reviews
Yan N
(2021)
Controls on fluvial meander-belt thickness and sand distribution: Insights from forward stratigraphic modelling
in Sedimentology
Description | We have developed a relational database of deep marine clastic architecture (i.e., a set of data describing sediments deposited at significant water depths in the deep sea) at a scale that its outputs are, in principle, reliable indicators of the disposition of such systems under a range of different boundary conditions, and organised in such a way as to facilitate the incorporation of the database into commercial products that can interface with the modelling programmes most commonly used to describe fluid flow within such sediments. |
Exploitation Route | Directly following on from the work funded by this award, the University of Leeds has signed a commercialisation agreement with PDS (UK) Ltd to incorporate the DMAKS database into its Ava Clastics modelling product, which is being marketed to the oil and gas industry. |
Sectors | Energy |
URL | https://pds.group/ava-clastics/ |
Description | The project has facilitated the development of a relational database of deep marine sedimentary architecture that has been licensed by Leeds University to PDS (UK) Ltd, who intend to incorporate it into their Ava Clastics product. This has been launched, incorporating the DMAKS database that was develped under the auspices of this award. |
First Year Of Impact | 2018 |
Sector | Energy |
Impact Types | Economic |
Title | Development of a standarised approach for the hierarchical classification of deep marine architecture |
Description | The goal in this project was to develop a database approach to aid characterisation of deep marine clastic sediments. This requires that published examples be digitised to a common standard - in turn requiring a standardised approach. This task was achieved under the auspices of the project via supervision of an associated PhD student, who has developed such an approach. The approach is in press (awaiting proof corrections so not yet citable). |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2018 |
Provided To Others? | Yes |
Impact | Internally, we have developed a standardised descriptive approach which has underpinned database expansion. It's premature to note external impacts. |
Title | DMAKS |
Description | The project facilitated the development of the Deep Marine Architecture Knowledge Store (DMAKS) to a scale where it's output was attractive to a commercial partner. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | No |
Impact | No direct impacts as yet - but a commercialisation deal has been signed, and impacts are anticipated through industry uptake of the resulting product. |
Description | Commercialization of FAKTS, SMAKS and DMAKS databases; partnership between University of Leeds and Petrotechnical Data Systems (2017) |
Organisation | Petrotechnical Data Systems (PDS) |
Country | Netherlands |
Sector | Private |
PI Contribution | Commercialization agreement whereby University of Leeds provides database technologies for three in-house developed databases to PDS for inclusion in their Ava Clastics software suite. The AvaClastics software is now being actively marketed. |
Collaborator Contribution | Provision of expertise in software development. |
Impact | Sale and marketing of AvaClastics. Involves sedimentology, sedimentary geology. |
Start Year | 2017 |
Title | The Deep Marine Architecture Knowledge Store (DMAKS) |
Description | DMAKS is a relational database containing information on deep marine architecture. It can be used to predict the likely disposition of deep marine sediments given prior knowledge of the conditions of formation, and can further be used to test models describing such dispositions or changes in disposition arising following changes in boundary conditions. Under the auspices of the current award it was upscaled to the point where it became commercially attractive. |
IP Reference | |
Protection | Protection not required |
Year Protection Granted | 2017 |
Licensed | Yes |
Impact | None as yet |
Title | Ava Clastics - addition of new database |
Description | Ava Clastics, developed by PDS Ltd, facilitates the construction of geological models of facies and facies architecture, calibrated against databases containing such data from a large number of peer-reviewed publications that detail such data. This award led to the addition of a new component database to Ava Clastics - the Deep Marine Architecture Knowledge Store (DMAKS). |
Type Of Technology | Software |
Year Produced | 2018 |
Impact | It's relatively early days, so premature to detail impacts. |
URL | https://pds.group/ava-clastics/ |
Description | Commercial partner visit |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | PDRA Marco Patacci visited the offices of commercial partner PDS in the Netherlands for a 2-day trip to review how best to incorporate the database enhanced via the project into PDS's Ava Clastics product |
Year(s) Of Engagement Activity | 2017 |