Gbenga Folorunso Oluyemi

Heavy Oil Recovery: A Cold Process Using CO2-EOR Technique

Owing to substantial improvement in enhanced oil recovery (EOR) technologies and significant decline in discovery of light and medium crude oil fields, the heavy oil development is progressively receiving considerable attention to fill the supply gap. Cold heavy oil production (CHOP) using captured carbon dioxide (CO2)-EOR technique was investigated using the state-of-the-art Integrated Product Modelling packages of Petroleum Experts as part of the Well Engineering Research Group unconventional oil reservoir management studies being undertaken at Robert Gordon University. Beyond ascertaining the feasibility of the CHOP using CO2-EOR, the objectives of the investigation were to establish the process requirements at the onshore facilities based on series of parametric studies and to enhance the understanding of the subsea integrated injection and production systems during the injection process. The injection system consisted of an injection well connected to a 240 km subsea pipeline transporting CO2 from an onshore compression station. The production system included a topside separator connected to the production well via a 2km riser. A broad range of reservoir production history was used and the simulation results indicate that heavy oil displacement was easily achievable under miscible conditions (i.e. high reservoir pressure), but the production trend was strongly influenced by the reservoir characteristics (i.e. GOR, WC, Pressure).

Conceptual physicochemical models for scale inhibitor-formation rock interaction.

The current oil industry approach to geomechanical evaluation of reservoir formations invaded by chemical inhibitors does not in any way take into consideration any potential effects of these chemicals on the reservoir formation fabrics. It is more often than not assumed that the interaction between chemical inhibitor species and sand materials is of no geomechanical significance. To investigate this, laboratory experiments were performed on Clashach cores representing clastic reservoir formation analogues. The experimental results show sand failure and release into the flow streams. Based on the experimental results conceptual physicochemical failure models are proposed for analyzing and describing the inhibitor-formation interaction.

UCS Neural Network Model for Real Time Sand Prediction

Exploration and production activities have moved into more challenging deep-water and subsea environments. Many of the clastic reservoirs in these environments are characterized by thick overburden, HP-HT and largely unconsolidated formations with challenging sand management issues. For effective overall field/reservoir management, it is crucial to know if and when sand would fail and be ultimately produced. Field-life sanding potential evaluation and analysis, which seeks to evaluate the sanding potential of reservoir formations during the appraisal stage and all through the development to the abandonment stage, is therefore necessary so that important reservoir/field management decisions regarding sand control deployment can be made. Recent work has identified Unconfined Compressive Strength (UCS) as a key parameter required for the evaluation and analysis of sanding potential of any reservoir formation. There is therefore the need to be able to predict this important sanding potential parameter accurately and in real time to reduce the level of uncertainties usually associated with sanding potential evaluation and analysis. In this work, neural network coded in C++ was trained with log-derived petrophysical, geomechanical and textural data to develop a stand-alone model for predicting UCS. Real-time functionality of this model is guaranteed by real time data gathering via logging while drilling (LWD) and other measurement while drilling (MWD) tools. The choice of neural network over and above other methods and techniques which have been widely used in the industry was informed by its ability to better resolve the widely known complex relationship between petrophysical, textural and geomechanical strength parameters.

Investigation of CO2 Sequestration during Cold Heavy Oil Production

CO2 sequestration during cold heavy oil production using captured carbon dioxide was investigated using REVEAL of Petroleum Experts. The results indicated that the CO2 release was influenced by the production phases. The prediction showed high CO2 retention in the first few years post start-up, followed by a gradual decline toward 16.5% post peak production. The recovery rate was strongly influenced by the reservoir characteristics, such as fluid properties, permeability, aquifer, and well completion. Horizontal wells provided better performance than vertical wells. The CO2 utilization and retention per barrel of heavy oil increased as the CO2 injection pressure increased.

The Prospect of Deepwater Heavy Oil Production Using CO2-EOR

The prospect of unconventional oil development has long been coming to offset the rapid decline of conventional crude. And looking ahead, the worry is already turning away from the onshore exploitation to the challenging offshore environment, with the question being whether the emerging technology can overcome the challenges of deep-water heavy oil production. In economics terms, the immiscible process shows a negative return, a longer payback time, and a low net present value. With an increased revenue through increased production, there is a degree of strong, dynamic, and appealing prospect to any future heavy oil development using miscible process.

A Novel Approach to Subsea Multiphase Solid Transport

Transportation of multiphase reservoir fluid through subsea tiebacks has gained considerable attention in recent years especially in the deep offshore and ultra deep offshore environments where there is increasing pressure on the operators to reduce development costs without compromising oil production. However, the main challenge associated with this means of transporting unprocessed reservoir fluids is the need to guarantee flow assurance and optimise production. Solids entrained in the fluid may drop off and settle at the bottom of horizontal pipe thereby reducing the space available to flow and causing erosion and corrosion of the pipeline. The problem has been largely attributed to insufficient flow velocity among other parameters required to keep the solids in suspension and prevent them from depositing in the pipe. The continuous changing flow patterns have introduced additional complexities dependent on gas and liquid flow rates. Acquisition of experimental data for model development and validation in multiphase flow has been largely focused on single and two phase flow. This has impeded our understanding of the behaviour and associated problems of three phase or four phase (oil, water, gas and solid) in pipes. The result is inappropriate solid transport models for three phase and four phase. In order to bridge this gap, the Well Engineering Research group at Robert Gordon University has initiated a project on integrated multiphase flow management system underpinned by comprehensive experimental investigation of multiphase solids transport. The project is aimed at developing precise/accurate sand transport models and an appropriate design and process optimisation simulator for subsea tiebacks. In this paper, the physics of the multiphase transport models being developed is presented. The models will allow for the prediction of key design and operational parameters such as flow patterns, phase velocity, pressure gradient, critical transport velocity, drag & lift forces, flow rate requirements and tiebacks sizing for transient multiphase flow. A new multiphase flow loop is being developed which will be used to generate experimental database for building and validating the theoretical models for use in a proposed integrated simulator for deepwater applications.

Real Time Evaluation of Sanding Potential

More than 70% of the world oil and gas are domiciled in unconsolidated reservoir rocks with a high risk of sand production. To manage the sanding problem it is important to answer such questions as “will the reservoir fail?”, “when will it fail?”, “what volume of sand will it produce?” and “where will the sand come from – from the sand face or from the reservoir rock matrix?” In order to predict whether sand production will be problematic, the Sand Management Research Team at The Robert Gordon University has developed a three-fold approach the details of which are presented in this paper. Firstly, two alternative methodologies have been adopted for evaluating the failure potential of reservoir sand. Secondly, an estimate of sand production volumes and rates as a function of reservoir management policy, operational procedures and time is required with the caveat that sand failure is not equal to sand production. Thirdly, it is operationally optimal to have this done in real time, and over the life cycle of the field. A critical issue for accurate sanding quantification is the precise prediction of stress magnitudes and orientation with varying reservoir pressure depletion. The Mohr-Coulomb failure envelope is deployed in this tool to model rock failure based on the critical porosity concept. In the alternate approach, Neural networks have consequently been used to develop models for predicting both UCS and grain size distribution in real time. Critical model outputs include grain size distribution of failed sand, sand mass produced, maximum sand rate and time to first sand production, drawdown and depletion at first sand production. The pinnacle of this model is the derivation of a SAND PRODUCTION FORECAST.The real-time predictions help Sand Management teams develop optimal design and optimal productions strategies in relations to when and where to initiate sand control, effective topside management and real-time management of reservoirs with sanding problems. Advanced Materials Research Online: 2007-06-15 ISSN: 1662-8985, Vols. 18-19, pp 293-300 doi:10.4028/www.scientific.net/AMR.18-19.293