Porosity and permeability prediction through forward stratigraphic simulations using GPM™ and Petrel™: application in shallow marine depositional settings

Otoo, Daniel; Hodgetts, David

doi:https://doi.org/10.5194/gmd-14-2075-2021

Articles | Volume 14, issue 4

https://doi.org/10.5194/gmd-14-2075-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/gmd-14-2075-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 14, issue 4

Development and technical paper

|

22 Apr 2021

Development and technical paper |

| 22 Apr 2021

Porosity and permeability prediction through forward stratigraphic simulations using GPM™ and Petrel™: application in shallow marine depositional settings

Daniel Otoo and David Hodgetts

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Final revised paper (published on 22 Apr 2021)
Preprint (discussion started on 24 Jun 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Porosity and Permeability Prediction through Forward Stratigraphic Simulations Using GPMTM and PetrelTM: Application in Shallow Marine Depositional Settings', Johannes Hommel, 24 Jul 2020
- AC1: 'Feedback on Interactive comment on “Porosity and Permeability Prediction through Forward Stratigraphic Simulations Using GPM™ and Petrel™: Application in Shallow Marine Depositional Settings” by Johannes Hommel.', Daniel Otoo, 03 Aug 2020
RC2: 'Porosity and Permeability Prediction through Forward Stratigraphic Simulations Using GPM™ and Petrel™: Application in Shallow Marine Depositional Settings', Brian Burham, 02 Oct 2020
- AC2: 'Feedback on Interactive comment on “Porosity and Permeability Prediction through Forward Stratigraphic Simulations Using GPM™ and Petrel™: Application in Shallow Marine Depositional Settings”', Daniel Otoo, 09 Oct 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Daniel Otoo on behalf of the Authors (23 Oct 2020)

ED: Referee Nomination & Report Request started (11 Nov 2020) by Andrew Yool

RR by Anonymous Referee #1 (19 Nov 2020)

Suggestions for revision or reasons for rejection

The authors did improve the manuscript, but especially the tables are still quite poorly formatted, some of them even seeming to be just screenshots of articles (Table 1. after Kieft et al. 2011) or maybe simulation output (Table 5.) and are blurry or not well formatted. I especially do not understand the formatting choice in Table 5. Why are the porosity and permeability values of the original model separately given in the right columns when they simply could be added as a row below or above the forward-modeling-based values? This makes understanding the table unnecessarily complicated and actively hinders the comparison of original-model and forward-modeling-based values!

Similarly, Figure 12 is blurry to a point that the labels are not easy to read.

I like the improvements in the description of the GPM processes, but they fall a bit short. I still miss the information on how GPM actually calculates e.g. "Steady Flow Processes" or "Unsteady Flow Processes". Both sections read rather like an instruction manual than a scientific article. It is nice to know, which parameters to set at boundaries, but in a scientific article, in my opinion, it matters much more to give the governing equations these parameters are necessary to solve for. For a scientific reader, I assume that the equation describing the "real life" process in the model is of great importance to understand the quality and reliability of the results gained by applying the model. The section "Diffusion Process" at least gives an equation. Having written all this, I am still not sure, what GPM actually does. I previously and until now assumed that it solves equations that I would describe as "sediment-transport/deposition equations". However, the equation in section "Diffusion Process" makes me question that as there, the topographic elevation seems to be the primary variable of the equation. Shouldn't the diffusion (or maybe also rather dispersion?) of sediment depend also (or even much more?) on sediment and hydraulic characteristics, like e.g. the sediment grain size or turbulences?

Also for the section "Sediment Accumulation" the general handling of this in GPM is described, but again more in an instruction-manual style. It does not help to understand what GPM actually does. How does it account for different sediment types? Does it do a mass balance of the sediment for each type between sediment entering and leaving a cell? What are the actual physical processes and resulting equations implemented in GPM?

I am unsure about the usual policy for this journal about modeling studies, but in my experience and opinion, at least the basic equations of the numerical models used should be described in an article or at least a reference to the equations in a manual or so should be given. I would also expect some detail on what are the primary variables the equations are being solved for.

There are still some spelling/formatting mistakes, e.g. in line 207: kieft et al., (2011)

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RR by Brian Burham (26 Nov 2020)

ED: Reconsider after major revisions (29 Nov 2020) by Andrew Yool

AR by Daniel Otoo on behalf of the Authors (06 Jan 2021) Author's response Author's tracked changes Manuscript

ED: Reconsider after major revisions (27 Jan 2021) by Andrew Yool

AR by Daniel Otoo on behalf of the Authors (05 Mar 2021) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (14 Mar 2021) by Andrew Yool

AR by Daniel Otoo on behalf of the Authors (15 Mar 2021) Manuscript

Short summary

The forward stratigraphic simulation method is used to predict lithofacies, porosity, and permeability in a reservoir model. The objective of using this approach is to enhance subsurface property modelling through geologic realistic 3-D stratigraphic patterns. Results show realistic stratigraphic sequences. Given this, we can derive spatial and geometric data as secondary data to constrain property simulation in a reservoir model. The approach can reduce the uncertainty of property modelling.