Integrated Production Model as a Tool for Optimization the Development Strategy of the Sakhalin Oil and Gas Condensate Field

2021 ◽  
Author(s):  
Oleksandr Doroshenko ◽  
Miljenko Cimic ◽  
Nicholas Singh ◽  
Yevhen Machuzhak
Keyword(s):  
History Matching ◽  
Effective Field ◽  
Production Optimization ◽  
Production Model ◽  
Production Forecast ◽  
Hydrocarbon Production ◽  
Integrated Production ◽  
Wellhead Pressure ◽  
Field Development ◽  
The Impact

Abstract A fully integrated production model (IPM) has been implemented in the Sakhalin field to optimize hydrocarbons production and carried out effective field development. To achieve our goal in optimizing production, a strategy has been accurately executed to align the surface facilities upgrade with the production forecast. The main challenges to achieving the goal, that we have faced were:All facilities were designed for early production stage in late 1980's, and as the asset outdated the pipeline sizes, routing and compression strategies needs review.Detecting, predicting and reducing liquid loading is required so that the operator can proactively control the hydrocarbon production process.No integrated asset model exists to date. The most significant engineering tasks were solved by creating models of reservoirs, wells and surface network facility, and after history matching and connecting all the elements of the model into a single environment, it has been used for the different production forecast scenarios, taking into account the impact of infrastructure bottlenecks on production of each well. This paper describes in detail methodology applied to calculate optimal well control, wellhead pressure, pressure at the inlet of the booster compressor, as well as for improving surface flowlines capacity. Using the model, we determined the compressor capacity required for the next more than ten years and assessed the impact of pipeline upgrades on oil gas and condensate production. Using optimization algorithms, a realistic scenario was set and used as a basis for maximizing hydrocarbon production. Integrated production model (IPM) and production optimization provided to us several development scenarios to achieve target production at the lowest cost by eliminating infrastructure constraints.

Caveats and Pitfalls of Production Forecast Uncertainty Analysis Using Design of Experiments

2021 ◽  
Author(s):  
Boxiao Li ◽  
Hemant Phale ◽  
Yanfen Zhang ◽  
Timothy Tokar ◽  
Xian-Huan Wen
Keyword(s):  
Design Of Experiments ◽  
Uncertainty Analysis ◽  
History Matching ◽  
Petroleum Industry ◽  
Production Forecast ◽  
Forecast Uncertainty ◽  
Field Development ◽  
Development Alternatives ◽  
Modeling Principles ◽  
Made In

Abstract Design of Experiments (DoE) is one of the most commonly employed techniques in the petroleum industry for Assisted History Matching (AHM) and uncertainty analysis of reservoir production forecasts. Although conceptually straightforward, DoE is often misused by practitioners because many of its statistical and modeling principles are not carefully followed. Our earlier paper (Li et al. 2019) detailed the best practices in DoE-based AHM for brownfields. However, to our best knowledge, there is a lack of studies that summarize the common caveats and pitfalls in DoE-based production forecast uncertainty analysis for greenfields and history-matched brownfields. Our objective here is to summarize these caveats and pitfalls to help practitioners apply the correct principles for DoE-based production forecast uncertainty analysis. Over 60 common pitfalls in all stages of a DoE workflow are summarized. Special attention is paid to the following critical project transitions: (1) the transition from static earth modeling to dynamic reservoir simulation; (2) from AHM to production forecast; and (3) from analyzing subsurface uncertainties to analyzing field-development alternatives. Most pitfalls can be avoided by consistently following the statistical and modeling principles. Some pitfalls, however, can trap experienced engineers. For example, mistakes made in handling the three abovementioned transitions can yield strongly unreliable proxy and sensitivity analysis. For the representative examples we study, they can lead to having a proxy R2 of less than 0.2 versus larger than 0.9 if done correctly. Two improved experimental designs are created to resolve this challenge. Besides the technical pitfalls that are avoidable via robust statistical workflows, we also highlight the often more severe non-technical pitfalls that cannot be evaluated by measures like R2. Thoughts are shared on how they can be avoided, especially during project framing and the three critical transition scenarios.

scholarly journals Model-based decision analysis applied to petroleum field development and management

2019 ◽  
Vol 74 ◽  
pp. 46 ◽  
Author(s):  
Denis José Schiozer ◽  
Antonio Alberto de Souza dos Santos ◽  
Susana Margarida de Graça Santos ◽  
João Carlos von Hohendorff Filho
Keyword(s):  
Risk Analysis ◽  
Decision Analysis ◽  
Reservoir Simulation ◽  
History Matching ◽  
Model Updating ◽  
Production Optimization ◽  
Optimization Under Uncertainty ◽  
Computational Time ◽  
Field Development ◽  
Development And Management

This work describes a new methodology for integrated decision analysis in the development and management of petroleum fields considering reservoir simulation, risk analysis, history matching, uncertainty reduction, representative models, and production strategy selection under uncertainty. Based on the concept of closed-loop reservoir management, we establish 12 steps to assist engineers in model updating and production optimization under uncertainty. The methodology is applied to UNISIM-I-D, a benchmark case based on the Namorado field in the Campos Basin, Brazil. The results show that the method is suitable for use in practical applications of complex reservoirs in different field stages (development and management). First, uncertainty is characterized in detail and then scenarios are generated using an efficient sampling technique, which reduces the number of evaluations and is suitable for use with numerical reservoir simulation. We then perform multi-objective history-matching procedures, integrating static data (geostatistical realizations generated using reservoir information) and dynamic data (well production and pressure) to reduce uncertainty and thus provide a set of matched models for production forecasts. We select a small set of Representative Models (RMs) for decision risk analysis, integrating reservoir, economic and other uncertainties to base decisions on risk-return techniques. We optimize the production strategies for (1) each individual RM to obtain different specialized solutions for field development and (2) all RMs simultaneously in a probabilistic procedure to obtain a robust strategy. While the second approach ensures the best performance under uncertainty, the first provides valuable insights for the expected value of information and flexibility analyses. Finally, we integrate reservoir and production systems to ensure realistic production forecasts. This methodology uses reservoir simulations, not proxy models, to reliably predict field performance. The proposed methodology is efficient, easy-to-use and compatible with real-time operations, even in complex cases where the computational time is restrictive.

A Methodology To Quantify the Impact of Uncertainties in the History-Matching Process and in the Production Forecast

2005 ◽  
Author(s):  
Celio Maschio ◽  
Denis Jose Schiozer ◽  
Marcos Antonio Antonio Bezerra de Moura Filho
Keyword(s):  
History Matching ◽  
Production Forecast ◽  
Matching Process ◽  
The Impact

scholarly journals Subsidence monitoring network: an Italian example aimed at a sustainable hydrocarbon E&P activity

2015 ◽  
Vol 372 ◽  
pp. 379-384 ◽  
Author(s):  
M. C. Dacome ◽  
R. Miandro ◽  
M. Vettorel ◽  
G. Roncari
Keyword(s):  
Local Community ◽  
Monitoring Network ◽  
Local Environment ◽  
Hydrocarbon Production ◽  
Field Development ◽  
Monitoring Plan ◽  
Italian Law ◽  
Subsidence Monitoring ◽  
The Impact ◽  
Field Production

Abstract. According to the Italian law in order to start-up any new hydrocarbon exploitation activity, an Environmental Impact Assessment study has to be presented, including a monitoring plan, addressed to foresee, measure and analyze in real time any possible impact of the project on the coastal areas and on those ones in the close inland located. The occurrence of subsidence, that could partly be related to hydrocarbon production, both on-shore and off-shore, can generate great concern in those areas where its occurrence may have impacts on the local environment. ENI, following the international scientific community recommendations on the matter, since the beginning of 90's years, implemented a cutting-edge monitoring network, with the aim to prevent, mitigate and control geodynamics phenomena generated in the activity areas, with a particular attention to conservation and protection of environmental and territorial equilibrium, taking care of what is known as "sustainable development". The current ENI implemented monitoring surveys can be divided as: – Shallow monitoring: spirit levelling surveys, continuous GPS surveys in permanent stations, SAR surveys, assestimeter subsurface compaction monitoring, ground water level monitoring, LiDAR surveys, bathymetrical surveys. – Deep monitoring: reservoir deep compaction trough radioactive markers, reservoir static (bottom hole) pressure monitoring. All the information, gathered through the monitoring network, allow: 1. to verify if the produced subsidence is evolving accordingly with the simulated forecast. 2. to provide data to revise and adjust the prediction compaction models 3. to put in place the remedial actions if the impact exceeds the threshold magnitude originally agreed among the involved parties. ENI monitoring plan to measure and monitor the subsidence process, during field production and also after the field closure, is therefore intended to support a sustainable field development and an acceptable exploitation programme in which the actual risk connected with the field production is evaluated in advance, shared and agreed among all the involved subjects: oil company, stakeholders and local community (with interests in the affected area).

Examining the Impact of Hydrocarbon Drainage on Completion and In-Fill Drilling Strategies in Unconventional Reservoirs

2015 ◽  
Author(s):  
Karthik Srinivasan ◽  
Midowa Gbededo ◽  
Hongxue Hue ◽  
Jayanth Krishnamurthy ◽  
Veronica Gonzales
Keyword(s):  
Stress Distribution ◽  
History Matching ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Production Model ◽  
Hydraulic Fractures ◽  
Pressure Depletion ◽  
Asymmetric Stress ◽  
The Impact

Abstract Evaluating the effects of asymmetric stress distribution around a lateral can greatly help optimize completion techniques and overall production from in-fill horizontal wells in unconventional shale and tight reservoirs. Several factors affect long-term production from in-fill drilled wells including but not limited to pressure depletion from produced wells, change of effective stresses in the depleted formation and interference between hydraulic fractures when the new in-fill wells are drilled, stimulated and brought into production. The study addresses a variety of key challenges that the unconventional oil and gas industry is looking to understand. These include understanding: How the presence of a depleted wellbore affects hydraulic fracture propagation from a nearby newly drilled wellHow refracturing considerations in a producing well are affected by hydrocarbon drainage and modified stress contrastsHow fracturing/refracturing pumping designs and volumes should be optimized to address the challenges surrounding the wellbore Under circumstances mentioned above, pressure distribution around the wellbore from hydrocarbon drainage was estimated by history matching production data over a certain period of time. Then the impact of various types of fracturing treatments on pressure depletion profiles from offset wells was studied using a fully numerical fracture simulator that is capable of handling asymmetric stress distribution around the lateral. Fracture geometries from this study were either asymmetric due to depletion on only one side of the lateral or longer due to increased stress contrast. These fracture geometries were fed to a production model to forecast long-term production from in-fill wells and study drainage patterns over time. Understanding these challenges provided a sub-surface perspective of how completion techniques should be optimized to get maximum hydrocarbon recovery from reservoirs consisting of laterals that have already been on production.

scholarly journals An Integrated Production Optimization Approach of a Natural Gas Filed in Bangladesh

2017 ◽  
Vol 29 (1) ◽  
pp. 34-39
Author(s):  
Mohammad Mojammel Huque ◽  
Mahbubur Rahman
Keyword(s):  
Chemical Engineering ◽  
Production Optimization ◽  
Oil Field ◽  
Recovery Factor ◽  
Production Model ◽  
Optimization Approach ◽  
Gas Field ◽  
Integrated Production ◽  
Development Scenarios ◽  
Production Strategies

This paper presents an integrated production model for a producing gas field in Bangladesh. Integrated production modeling is a powerful method for optimizing gas or oil field production planning. This approach combines the reservoir performance, well inflow and outflow relationship and the surface facilities in a single platform to cover all operating envelopes and constrains. Once the model is established and validated, the production forecasts can be generated to study alternative development scenarios against reservoir performances. This allows choosing an optimum production strategy from different options. The method is computationally intensive, therefore commercial software packages are used to conduct this study. PROSPERTM, MBALTM and GAPTM modules from the IPM software suite were used to carry out this work. The current production strategies predict recovery factor of 49.38 % and 40.46% from Upper Gas Sand (UGS) and Lower Gas Sand (LGS) respectively, for next 25 years. An attempt to increase production from this field was considered in this study, since the field is producing only 50 MMCFD while the installed process plant capacity of 220 MMCFD. Several production strategies have been investigated that includes change in the tubing size of existing well, setting up new wells and addition of compressor facilities. Plateau production and ultimate recovery for next 25 years were compared for these scenarios. Initially change in the tubing sizes has been studied for well # 1 in UGS and well # 3, 4 in LGS gives 16% and 3% increase in ultimate recovery from current tubing condition respectively. The effect of adding two infill wells in UGS and two in LGS has also been studied. With additional wells, the ultimate recovery factor increases to 68.5% and 57 % for UGS and LGS respectively. Using compressor and infill wells shows the recovery of 92% for UGS and 71% for LGS respectively.Journal of Chemical Engineering, Vol. 29, No. 1, 2017: 34-39

scholarly journals Obtaining High Quality SCAL Data: Combining Different Measurement Techniques, Saturation Monitoring, Numerical Interpretation and Continuous Monitoring of Experimental Data

2019 ◽  
Vol 89 ◽  
pp. 02007 ◽  
Author(s):  
Yingxue Wang ◽  
Shehadeh K. Masalmeh
Keyword(s):  
Capillary Pressure ◽  
Relative Permeability ◽  
History Matching ◽  
Measurement Techniques ◽  
Poor Quality ◽  
Production Forecast ◽  
Raw Data ◽  
Field Development ◽  
Core Samples ◽  
Phases Of Development

SCAL parameters (i.e., Relative Permeability and Capillary Pressure curves) are key inputs to understand and predict reservoir behavior in all phases of development. Techniques to measure relative permeability and capillary pressure have been well established and applied to a wide variety of core samples both from sandstone and carbonate reservoirs. On the other hand, we frequently encounter quality compromised data due to challenges in experimental procedures, lack of understanding of measurement techniques, and poor quality of raw data. As a result, relative permeability is often viewed as a parameter with large uncertainties and a fitting parameter in history matching. A special core analysis program was recently carried out on selected core samples from a deep-water sandstone reservoir in the Gulf of Mexico. In this frontier, relative permeability has been ranked among the top subsurface uncertainties. It greatly impacts the production forecast and field development plan. However, due to the high temperature, high salinity and fluid compatibility issues, the core measurements faced very specific challenges and a good relative permeability dataset has not been obtained in the past for this area. In this work, we demonstrate that a quality set of relative permeability data can be obtained through close collaboration across disciplines, a properly designed protocol, adequate engagement with the laboratory, timely QA/QC of experimental raw data, and appropriate interpretation incorporating numerical simulations. Well-defined and constrained relative permeability curve shave been derived with the combination of steady state and centrifuge techniques. The average trend can be described by a residual oil saturation of 22%, end-point relative permeabilities of 0.6 and 0.2 to oil and water, respectively and Corey exponents between 2 and 3.

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