The 2016 SPE International Student Paper Contest was held at the SPE Annual Technical Conference and Exhibition (ATCE) in Dubai and the following papers are announced winners. These papers will be published in the ATCE conference proceedings and on OnePetro, a multisociety technical library for the oil and gas exploration and production industry. Winners of the 14 SPE Regional Student Paper Contests from each division competed for the international recognition. "Wellbore Stability Analysis Based on Sensitivity and Uncertainty Analysis" by Fernando Antonio Plazas Niño, Universidad Industrial de Santander
A new real-time machine learning model has been developed based on the deep recurrent neural network (DRNN) model for performing step-down analysis during the hydraulic fracturing process. During a stage of the stimulation process, fluids are inserted at the top of the wellhead, while the flow is primarily driven by the difference between the bottomhole pressure (BHP) and reservoir pressure. The major physics and engineering aspects involved are complex and, quite often, there is a high level of uncertainty related to the accuracy of the measured data, as well as intrinsic noise. Consequently, using a machine learning-based method that can resolve both the temporal and spatial non-linear variations has advantages over a pure engineering model.
The approach followed provides a long short-term memory (LSTM) network-based methodology to predict BHP and temperature in a fracturing job, considering all commonly known surface variables. The surface pumping data consists of real-time data captured within each stage, such as surface treating pressure, fluid pumping rate, and proppant rate. The accurate prediction of a response variable, such as BHP, is important because it provides the basis for decisions made in several well treatment applications, such as hydraulic fracturing and matrix acidizing, to ensure success.
Limitations of the currently available modeling methods include low resolution BHP predictions and an inability to properly capture non-linear effects in the BHP/temperature time series relationship with other variables, including surface pressure, flow rate, and proppant rate. In addition, current methods are further limited by lack of accuracy in the models for fluid properties; the response of the important sub-surface variables strongly depends on the modeled fluid properties.
The novel model presented in this paper uses a deep learning neural network model to predict the BHP and temperature, based on surface pressure, flow rate, and proppant rate. This is the first attempt to predict response variables, such as BHP and temperature, in real time during a pumping stage, using a memory-preserving recurrent neural network (RNN) variant, such as LSTM. The results show that the LSTM can successfully model the BHP and temperature in a hydraulic fracturing process. The BHP and temperature predictions obtained were within 5% relative error. The current effort to model BHP can be used for step-down analysis in real time, thereby providing an accurate representation of the subsurface conditions in the wellbore and in the reservoir. The new method described in this paper avoids the need to manage the complex physics of the present methods; it provides a robust, stable, and accurate numerical solution throughout the pumping stages. The method described in this paper is extended to manage step-down analysis using surface-measured variables to predict perforation and tortuosity friction.
This seminar will teach participants how to identify, evaluate, and quantify risk and uncertainty in everyday oil and gas economic situations. It reviews the development of pragmatic tools, methods, and understandings for professionals that are applicable to companies of all sizes. The seminar also briefly reviews statistics, the relationship between risk and return, and hedging and future markets. Strategic thinking and planning are key elements in an organisation’s journey to maximise value to shareholders, customers, and employees. Through this workshop, attendees will go through the different processes involved in strategic planning including the elements of organisational SWOT, business scenario and options development, elaboration of strategic options and communication to stakeholders.
The difficulty in applying traditional reservoir-simulation and -modeling techniques for unconventional-reservoir forecasting is often related to the systematic time variations in production-decline rates. This paper proposes a nonparametric statistical approach to resolve this difficulty. In this work, the authors perform automatic decline analysis on Marcellus Shale gas wells and predict ultimate recovery for each well.
Digital technologies serve as a primary theme of this year’s group, with a few environmentally conscious firms included in the mix. The large independent put together a team of data scientists, software developers, and petrotechnical staff to create a forward-looking vision for how to use digital technology to solve problems. Do women in academia face the same challenges as their peers in industry? Using maglev technology, a new artificial lift system seeks to boost production output by sucking down reservoir pressure from inside the wellbore and from inside the reservoir. The projects are designed to reduce technical risks in enhanced oil recovery and expand application of EOR methods in conventional and unconventional reservoirs.
It will provide re ... Harkand has secured a USD 5 million contract from Swiber Offshore Mexico to perform saturation divin ... Two Bumi Armada subsidiary companies secured USD 300 million worth of contracts from ElectroGas for ... Amec Foster Wheeler has been awarded a contract by BP worth more than USD 73 million. Tam International, which provides inflatable and swellable packers for the oil and gas industry, has ... Sanchez Energy closed a deal with a subsidiary of Sanchez Production Partners to sell wellbore and a ... Penn West Petroleum has entered into a USD 321 million agreement with Freehold Royalties to sell an ... Bonterra Energy has acquired Cardium formation-focused assets in the Pembina area of Alberta, Canada ... Petrobras has sold its assets in Argentina’s Austral basin to Compañia General de Combustibles for U ... Pemex signed an agreement worth USD 1 billion with private equity firmFirst Reserve to jointly inves ... Gulfport Energy entered into an agreement to acquire Paloma Partners III for USD 300 million. Apache sold its 13% stake in the Wheatstone LNG terminal in Western Australia and 50% interest in th ... Shell Petroleum Development Company of Nigeria completed the sale of its 30% interest in Oil Mining ... Oil and gas safety company Secorp opened a new office in Hobbs, New Mexico. Bill Barrett Corp. has signed agreements with several undisclosed recipients for the sale of the maj ... Encana said it will sell its remaining 54% stake in PrairieSky Royalty via a USD-2.4-billion Cardinal Energy entered into an agreement with an unnamed seller to acquire assets whose total daily ... Petrobras has awarded a contract, worth USD 465 million over a period of 5 years, to Aker Oilfield S ... CGG received contracts for the 3D seismic acquisition of four surveys using its marine broadband tec ... IKM Subsea, a subsidiary of IKM Group, has been awarded a contract by Eni Indonesia to provide remot ... OneSubsea, Schlumberger, and Helix Energy Solutions signed a letter of intent to develop technologie ... Premier Hytemp has committed to opening a USD-20-million, 67,000-ft2 precision engineering facility ... Expro has constructed a new 20,000‑m2 facility in Macaé, Brazil.
This paper describes a coreflooding program performed with sandpacks at different permeabilities, water qualities, and injection conditions. ProSep’s Osorb Media Systems are providing a unique solution for treating the water coming from chemical enhanced oil recovery operations and removing the dissolved hydrocarbons. Rising oil production in the Permian Basin has created an opportunity for midstream companies to acquire and expand pipeline infrastructure to handle a predicted spike in produced water. The company makes good on a pledge to reduce freshwater use and replenish the fresh water it uses. In a recent acquisition, H2O Midstream will own and operate Encana’s produced-water gathering system in Howard County, Texas, and will expand it to also serve third parties.
Big-data mining techniques can help determe the type-curves and the resulting estimated ultimate recovery of an asset being evaluated for acquisition. In this work, the authors perform automatic decline analysis on Marcellus Shale gas wells and predict ultimate recovery for each well. In this work, the authors perform automatic decline analysis on Marcellus Shale gas wells and predict ultimate recovery for each well.