Next-shot@Geomodeling - Because Geology Matters

This picture summarizes our 2024 work on our unique data-driven C-FSM (Constrained - Forward Stratigraphic Modeling) technology. These five case studies bring the total number of our test cases to fifteen. As we start 2025, we wish all our current and future followers a great year. For us in 2025, we already have three case studies planned, and if anybody wants to give us a modeling challenge, we will gladly consider it. Thanks. #geologicalmodeling, #reservoirmodeling

Data-Constrained Forward Stratigraphic Modeling of Carbonates: We continue to focus on modeling the vertical and horizontal heterogeneity of carbonate deposits constrained by lithofacies interpretations. In this example, with height wells, the vertical variation is at the meter scale, and the horizontal variation is at the 10m scale. Vertically and horizontally, we move from back-ramp deposits to calmer lagoon deposits in the Arab-D formation and from inter-tidal channel to non-channel deposits to supra-tidal deposits in the Arab-C formation. We constrain the deposition landscape so that the modeled environment matches the intervals' lithofacies by controlling the topography, sea-level variation, and channel proximity. The cross-section shows how we match every interval. We compute attributes such as wave or tidal energy influencing the granulometry. Super-imposed, we compute and visualize the effect of sea-level variation on diagenesis potential at every location. The reservoir grid layers are then built from the deposition geometries. The computed attributes can be used as trends for reservoir properties like porosity and permeability. The data are taken from an outcrop study by H. Eltom et al. Thanks for your continued support. It is much appreciated. #geologicalmodeling

The video shows the C-FSM modeling of a carbonate deposition sequence starting from Upper Jubaila lower-slope deposits, then Arab-D back ramp and lagoon deposits, and ending with Arab-C tidal-flat deposits. The data are from a study of the Wadi Nisha outcrop by A. Heltom et al. As the area to model is relatively small, we model a larger area at a coarser scale to better visualize and inform the local deposition environment. In this example, the deposition bodies are built at four different scales, illustrating the muti-scale aspect of C-FSM. The input data consists of eight wells with three parasequences of lithofacies. The sea-level curve is computed to match the bathymetry requirements, and the deposition is calculated by the associated deposition processes, which are controlled by the interval thickness and rock type. The deposition processes compute the relative granulometry of the deposits, either controlled by the wave energy for the upper-slope vs. back ramp vs. lagoon deposits or the distance to the tidal channels for the inter-tidal deposits. As always, thanks for your support. #geologicalmodeling

This example focuses on controlling tidal channel deposits from lithofacies in a tidal-flat environment. We use the Arab-C Wadi Nisah Outcrop study used in the last post. We have eight control wells. The first three layers only include mudstone deposits. The second layer has mudstone, grainstone, and breccia deposits with no obvious horizontal correlation (even if the well's spacing is less than 20 meters). The third layer is only composed of mudstone and grainstone. We associate the grainstone with tidal channel proximity and the breccia to supra-tidal deposits. We use grainstones vs. mudstone intervals to constrain the tidal channels network location and deposits. The grainstones control the local presence of channel bars. The supra-tidal deposits influence the topography, so they are above the intertidal zone. As the image shows, every well's interval is honored, and the constrained deposition process controls the deposition heterogeneity. As in all our other case studies, we tailor our modeling objects and processes to the deposition environment to match the heterogeneity. As always, thanks for your support. #geologicalmodeling #reservoirmodeling

Starting from Mudstone, Breccia, and Wavy Grainstone intervals interpreted as part of carbonate tidal flats (inter-tidal and supra-tidal) deposits on 12 pseudo-wells, we construct a constrained tidal-flat deposition model of the Arab-C formation using our C-FSM method. First, the lithofacies constrain tidal channel locations and transport at each deposition step. Second, we model the intra-tidal deposits by diffusion away from the tidal channels. Then, storm-induced higher tide levels carry supra-tidal deposits above the tidal deposits. As only three wells (N-3, N-4, N-11) carry these supra-tidal deposits, the supra-tidal deposition is only linked to the nearby channels supporting higher-grade sediments' transport. This example again shows the power of our method in introducing realistic spatial heterogeneity while fitting to the input data. The modeled deposits' heterogeneity is linked to the diffusion process as the tide transports sediment along and away from the tidal channels. We automatically compute the high-frequency sea-level variations required to alternate between mudstone and breccia deposits from the input parasequences. Thanks for your continued support. #geologicalmodeling #carbonatemodeling

We have joined OSDU and aim to expand OSDU's geological footprint in the well and seismic interpretation domains. 1️⃣ To start, we will work to improve the OSDU depositional environments dictionary to make it easier to code and decode. 2️⃣ We also need to introduce the notion of well's depositional sequences and hierarchy in OSDU and Resqml wells. 3️⃣ Third, we need to augment the classification of geologic features to support the paleo-landscape elements we can interpret on a paleo-slice interpretation and then use in C-FSM. It will be a long road, as both OSDU and Resqml need updating, but we have taken the first step😊.

Moving on to Carbonate modeling, we use the Wadi Nisha outcrop study by H. Eltom et al. to model the upper Jubalia and lower Arab-D deposits from the sedimentary logs. The evolution of the carbonate platform deposits is driven by the sea level, which we compute from the lithofacies. The local bathymetry, induced from the lithofacies, constrains the geometry of the platform slope in the upper Jubalia and the lagoon back ramp in the lower Arab-D. The back ramp geometry influences the wave energy on the upper slope, defining local lithology trends. As we see in the image, each layer's boundaries are perfectly honored, providing stratigraphic information for the reservoir model. The computed trends (wave energy, bathymetry, local environment) will constrain the reservoir model's petrophysical properties simulation, introducing process-based realistic heterogeneities. As always, thanks for your support. #geologicalmodeling #forwardstratigraphicmodeling #reservoirmodeling

Following our examples, we describe the C of our C-FSM method, which stands for Constrained Forward Stratigraphic Modeling. The table below shows how we translate geologic, seismic, and production interpretation into constraints to construct a paleo-stratigraphic model. Each data type defines pieces of the geological deposition landscape at different horizontal and time scales. - Unlike traditional FSMs, unconstrained, our models can be directly used to create reservoir models, replacing facies modeling and providing detailed stratigraphy. - Unlike traditional FSMs, our models are fast to compute and simple to set up. The constraints provide the sedimentary information, which is typically challenging to give with conventional FSMs. As an example of ease of use, the last turbidite deposit example took one day to construct, and each scenario took minutes to complete. So, improving geomodeling is possible, and we will continue on our journey to prove that in many different geological environments. As always, thanks for your support. #geologicalmodeling #reservoirmodeling

Beyond seismic, Production data can control the geological model created by our C-FSM method. Seismic interpretation provides information about the location of "deposition bodies complex,” while production data interpretation provides information about their shape/organization. The two examples below show how production information interpretation controls the river meanders evolution, as we change well to well connectivity or well productivity. With our C-FSM method, it is possible to integrate all information types, seismic, geology, and production, as never before, into a geological and reservoir model. As always, thanks for your support. #geologicalmodeling, #reservoirmodeling #reservoirgeology

We use our C-FSM method to model turbidite deposits from a few proportion control points interpreted on a seismic map from Hong‐Xia Ma et al.'s publication in the Rakhine Basin. We examine the influence of lobe shape parameters on the output net-to-gross maps computed from the stacked deposits. We use seven control lithofacies proportions interpreted from the RMS attribute map to constrain the simulation. The deposition is also constrained by the paleo-topography informed by the seismic image. The seismic provides only a view of the deposition complex, and the goal is to reconstruct the deposition story. Each realization takes 2mn to compute, so comparing different realizations to evaluate different interpretations and scenarios is easy. The image below shows two scenarios of lobe shape dimensions referred to in the original paper as frontal splay with either a lobate or elongated shape. The interesting element of the simulation is how we match the seismic and how the lobe shapes are potentially connected under various scenarios. Of course, the broader lobes will provide better horizontal connectivity. And the broader lobe shapes also seem to fit the seismic image better. As always, thanks for your support. #geologicalmodeling