Several mathematical ROP models were developed in the last five decades in the petroleum industry, departing from rather simple but less reliable R-W-N (drilling rate, weight on bit, and rotary speed) formulations until the arrival to more comprehensive and complete approaches such as the Bourgoyne and Young ROP model (BYM) widely used in the petroleum industry. The paper emphasizes the BYM formulation, how it is applied in terms of ROP modeling, identifies the main drilling parameters driving each subfunction, and introduces how they were developed; the paper is also addressing the normalization factors and modeling coefficients which have significant influence on the model. The present work details three simulations aiming to understand the approach by applying the formulation in a presalt layer and how some modification of the main method may impact the modeling of the fitting process. The simulation runs show that the relative error measures can be seen as the most reliable fitting verification on top ofR-squared. Applying normalization factors and by allowing a more wide range of applicable drillability coefficients, the regression could allow better fitting of the simulation to real data from 54% to 73%, which is an improvement of about 20%.

Pre-salt layers has long-term exploration and production possibilities, however the properties of such layers are highly challenging for exploration (i.e. these carbonate layers are highly abrasive, located deeper than 5000 m, have generally low permeability) and production (i.e. pre-salt layers are located in harsh oceanic conditions, hundreds of km offshore). These conditions mean increased exploration technological and economic difficulties. One of the partial solutions to decrease costs is to reduce the drilling operations time. Rate of penetration (ROP) has a significant effect on the overall drilling time, driving ROP modeling and optimization to be a viable solution for reducing drilling operations time in such environment. Several mathematical ROP models were developed in the last five decades in the petroleum industry, departing from rather simple but less reliable R-W-N (drilling-rate, weight-on-bit and rotary-speed) equations until the arrival to a comprehensive and complex approach: Bourgoyne and Young ROP Model (BYM) which was first published in 1974. The paper explains the equation, how it is applied in terms of ROP modeling, identifies the main drilling parameters driving each sub-functions, and introduces how they were developed. The paper base itself on the sub-functions of the equation, explains the normalization factors which have significant influence on the model, and also introduces simulations which aim to understand the approach by applying the equation in a pre-salt layer case study. Knowing that, the original publication was introduced in 1974, this paper also aims to identify rooms for improvement and/or alternate the sub-functions to match actual field data better than with the originally given drillability coefficient recommended boundaries stated in the first publication. This is accomplished through a real-world practical application of this ROP model in a pre-salt layer. The paper also assesses the limitation in terms of the applicability of this complex model for ROP analysis and optimization in such carbonate layers.

In software design, the various stakeholders generate large numbers of heterogeneous artifacts. These artifacts are often developed in, and managed by, different tools. In this paper, we present our initial prototype of Linecept, a tool that helps stakeholders organize, find, and view disparate design artifacts by organizing them on a timeline that presents a single unified view of the artifacts and who created them. We have used Linecept to retrospectively capture design artifacts for its own creation and in a software design class. CCS CONCEPTS • Software and its engineering → Software design engineering; • Human-centered computing → Interaction design process and methods; Visualization systems and tools; • Applied computing → Computer-managed instruction.

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