The GOM3 Analytics Addon is a collection of tools to bring high end analytics and visualization to different groups working in the Gulf of Mexico. Building on top of the rich database of GOM3, and the experience of continuously expanding the features therein, the Analytics Addon is designed to streamline workflows at a time when everyone is trying to maximize efficiency.
This package includes analyses for a variety of users, from forecasts of lease sale bidding, to pipeline routing using seafloor bathymetry and hazards, to visualization of well logs both online and in 3D GIS scenes. Below is the description of the Bidding/Block Evaluation Addon, but we are always available to show these in a live demo (the best way to view the dynamic tools).
Earth Science Associates developed two models for forecasts of bids in future sales. The first estimates the probability of at least one bid on deep water blocks. Block characteristics, from water depth to proximity of relinquished leases, to the history of past bids, have all been tabulated and are updated daily as changes occur. Additionally, there are global variables (e.g., oil price) and company-specific variables (e.g., how far is the nearest lease owned by ENI?). In all, we evaluated two dozen variables.
For the 20 companies that dominate deep water, we calculate the marginal positive and negative preferences toward these block characteristics, as seen below.
The tornado plot identifies the explanatory variables (listed along the y-axis) shown to be statistically significant in estimation of bid likelihood for Shell in the spring 2018 sale. A positive estimate results in an increase of probability of bidding and a negative estimate decreases the probability of bidding.
Some companies are less likely to bid in deeper waters, others systematically stay close to their existing leases. The company-level analyses of each block are then combined to esti-mate the probability that each block will receive at least one bid. We call this the Bid/No-Bid model. It is estimated using logistic regressions.
A map of estimated probability of at least one bid in the Spring 2018 sale, focused on northern Green Canyon. Current Leases are shown in grey, ESA’s pre-sale probabilities of bids are shown in the legend colors and those blocks actually bid are surrounded by thick, black outlines.
The second model, shown below, forecasts the amount of the high bid in deep water blocks. Like the Bid/No-Bid model, empirical block characteristics and companies’ historically evidenced preferences are included in the Bid Amount model. This model is estimated with a multivariate linear regression of past bids.
These regression models train over specific periods, which the user controls. Any period since 2009 of at least three years can be used to train the models to forecast for 2013 through the upcoming sale. For the historical sales (2013 and spring 2018 sale), forecasts can be made to compare the forecasted probability of Bid and Bid Amount with what actually occurred in the sale.
A map of the forecasted high bid amount in the spring 2018 sale, focused on northern Green Canyon. ESA’s estimated bid amounts are shown in the legend colors.
These two models provide systematic analysis of bidding behavior and an objective set of updated benchmarks, on constantly updated information, to analyze your competitors and examine the relative attractiveness of regions and blocks within them. Through the power of GOM3, model results can be combined with the data and tools there and, more importantly, with your company’s proprietary geoscience, engineering and scouting information – as well as a company strategy.
Why ponder a big, static war-room wall map when you can use state-of-the-art models based on data refreshed daily?