1. Updating 3D Reservoir Models with Log Data Inversion Results from High-Angle and Horizontal Wells Interpretation of Electromagnetic measurements in high-angle and horizontal (HA/HZ) wells relies on physics-based forward modeling. Typical HA/HZ well scenario is shown in Figure 1. Complexities seen by the logging tools include lateral changes in reservoir fluids; well trajectory inclination and azimuth; lateral lithology changes; nonparallel bed boundaries with variable dip & azimuth; faults or fractures; Log modeling is enabled by an integrated high- performance computing (HPC) environment (Figure 2 on the left) with a distributed Web-based architecture to provide ubiquitous remote access to 3D simulation and inversion on a grid or cloud. It can be easily embedded into any geological modeling platform as a plug-in. Examples of such client applications are shown in Figure 4 below. Conclusions V. Polyakov, D. Omeragic, S. Shetty, Schlumberger; B. Brot, EPFL; T. Habashy, A. Mahesh, T. Friedel, T. Vik, T. L. Flugsrud, Schlumberger Figure 1. Well-log interpretation in HA/HZ wells includes faults, nonparallel boundaries, lateral property changes, cross-bedding, anisotropy, and complex invasion shapes. Reservoir Model Update Workflow finite-size, thin conductive or resistive streaks; cross- bedding with variable dip and azimuth; and complex “tear-drop” invasion (see Figure 5 below for more on invasion). Once interpreted, despite the wealth of information contained therein, horizontal well logs are rarely considered in refining geological models. Difference of scales between reservoir models and log data is one of the major reasons. Current practice by selected experts is to painstakingly do it manually, if at all; that results in models that do not honor high-resolution data. Our goal is to incorporate log inversion results in the vicinity of the borehole into the 3D geological model, in the workflow depicted in Figure 3 to the right. Client Applications C++, C# Matlab, Python, … Proxy Grid Agents RunSimulator() = Web service protocol Simulation Service Modeling Web Service Well-log Modeling Codes Callback Service simulation job depth1 … depth n Grid Framework Server CPU 1 Core1 Core2 CPU 2 Core1 Core2 Core4 CPU depth i depth i+3 Core3 Core2 Core1 GPU4 GPU3 GPU2 GPU1 GPU workstation Grid Agents Figure 2. Log modeling and inversion codes reside on a network resource and are available as a Web service to geomodeling applications (top of the picture). On the back end of this integrated environment is a distributed, platform-independent HPC infrastructure where parallelized simulators are executed. Any cluster, multi-core PC, or GPU workstation can be part of the grid. To make geomodel consistent with log data, changes in geometry and properties on 2D curtain need to be propagated to 3D pillar grid. The problem is overdetermined. An optimal fit is found automatically, taking into consideration a number of options for mapping 2D projections back to their 3D source. Main and transition zones are defined (Figure 6); Figure 6. Illustration of the concept of propagating changes made on 2D curtain back to 3D grid. Two zones are defined: main and transition. In main zone, all changes made in the curtain are honored when the new geometry is calculated. Transition zone serves as a buffer to smooth out changes both in geometry and properties. Through this workflow, we arrive at geomodels that honor both seismic and resistivity well-log data. The combination, in a single workflow, of physics- based log modeling codes, Services-Oriented Architecture, HPC framework, and the solver to optimally retrofit 2D cross-sections into 3D models, creates a qualitatively new opportunity for geologists and reservoir engineers. This integrated workflow maximizes the value of well-logs incorporating them into the source of data for building geomodels. It also radically speeds up the model refinement loop and enables geoscientists to directly refine geomodels while geosteering or doing formation evaluation. (cont’d) changes in the former are applied directly, whereas in the latter they are gradually smoothed to the boundary of the unchanged region (Figure 6, left). Nodes and pillars of the 3D grid are automatically moved to their new calculated locations; similarly, property changes are applied (Figure 8, right) as a result of user interaction depicted in Figure 7 above. Figure 7.User interface for interacting with the model update component. First selection is to choose the pillar grid and the well; next, extent of the curtain section is specified as trajectory start and stop measured depths and vertical distance from the trajectory; next, vertical and lateral extent of the transition zone is specified; finally, the user chooses the method to propagate 2D geometry changes to 3D, and the grid update calculation is launched. Ocean/Petrel Web browser Matlab Techlog Figure 5. Geological models typically do not include near-borehole features such as invasions, which are essential for formation evaluation applications, since presence of an invaded region around the borehole can substantially affect the logs. We have integrated an invasion model into a reservoir model via a custom domain object. The picture on the left illustrates editing the invasion profile at different depths. The profile can have a parametric or arbitrary shape, allowing complex models in HA/HZ, such as tear-drop invasions. Multiple fronts and invasion events (insert on the left picture) can be defined to aid time-lapse interpretation of permeability, and, integrated with other drilling information, may provide useful information about wellbore stability while drilling. To assist manual invasion definition, borehole images can be mapped onto the well surface, as well as the invasion shapes, as shown on the right picture. Figure 8. Pillar grid before the change is applied (top left) and after (top right). Bottom pictures show the “model delta” object—a visualization of the extent of the change in the pillar grid. The disks are located on the pillar nodes. Their size and color intensity are proportional to the absolute change in the node position in XYZ space. The disks are largest in the main zone and taper out in the transition zone to eventually zero size. On the bottom left picture, it is easy to see that the change to the model was done only on one side of the fault. The orientation of the disks indicates the direction in which the node shifted: horizontal disks mean that only Z coordinate had changed; tilted disks signal that X and Y coordinates had also changed. Figure 4. Some examples of client applications enabled by the Integrated log modeling and inversion infrastructure. All of them use the same back-end computational engine as a Web service. Figure 3. Proposed workflow loop to interpret HA/HZ based on reservoir model and then update the latter. 3D geological model is used as the starting point for interpreting logs. A near-wellbore region is extracted as a 2D “curtain” cross-section, parameterized, and updated in the process of inversion. The two bottom figures illustrate changes in the model resistivity, applied to both vertical and lateral profiles, and some change in the dip. As the last step, the changes from the curtain are propagated to the 3D pillar grid. Fault