Integrated Subsurface to Surface Modeling to Assess Reservoir Uncertainty Quantification to A Carbonate Reservoir

2020 ◽  
Author(s):  
A. Chaterine
Keyword(s):  
Uncertainty Quantification ◽  
Gas Production ◽  
Carbonate Reservoir ◽  
Production Volume ◽  
Production Forecast ◽  
Uncertainty Range ◽  
Field Development ◽  
Production Forecasting ◽  
Production Scheme ◽  
Rock Compressibility

This study accommodates subsurface uncertainties analysis and quantifies the effects on surface production volume to propose the optimal future field development. The problem of well productivity is sometimes only viewed from the surface components themselves, where in fact the subsurface component often has a significant effect on these production figures. In order to track the relationship between surface and subsurface, a model that integrates both must be created. The methods covered integrated asset modeling, probability forecasting, uncertainty quantification, sensitivity analysis, and optimization forecast. Subsurface uncertainties examined were : reservoir closure, regional segmentation, fluid contact, and SCAL properties. As the Integrated Asset Modeling is successfully conducted and a matched model is obtained for the gas-producing carbonate reservoir, highlights of the method are the following: 1) Up to ± 75% uncertainty range of reservoir parameters yields various production forecasting scenario using BHP control with the best case obtained is 335 BSCF of gas production and 254.4 MSTB of oil production, 2) SCAL properties and pseudo-faults are the most sensitive subsurface uncertainty that gives major impact to the production scheme, 3) EOS modeling and rock compressibility modeling must be evaluated seriously as those contribute significantly to condensate production and the field’s revenue, and 4) a proposed optimum production scenario for future development of the field with 151.6 BSCF gas and 414.4 MSTB oil that yields a total NPV of 218.7 MMUSD. The approach and methods implemented has been proven to result in more accurate production forecast and reduce the project cost as the effect of uncertainty reduction.

Static and Dynamic Uncertainty Management for Probabilistic Production Forecast in Chuchupa Field, Colombia

2007 ◽  
Vol 10 (04) ◽  
pp. 433-439 ◽  
Author(s):  
Nestor Rivera ◽  
Nestor Saul Meza ◽  
Jeoung Soo Kim ◽  
Peter Andrew Clark ◽  
Raymond Garber ◽  
...  
Keyword(s):  
Simulation Models ◽  
Gas Production ◽  
Reservoir Model ◽  
Production Forecast ◽  
Water Contact ◽  
Wide Range ◽  
Static Models ◽  
Static Modeling ◽  
Optimization Routine ◽  
Rock Compressibility

Summary Structural, stratigraphic, and petrophysical uncertainties result in a wide range of geologic interpretations. For fields with a long production and pressure history, 3D dynamic simulations have been very useful in providing feedback to geologic modelers, which results in improved static models. For this study, we developed an integrated static and dynamic workflow to create a range of probabilistic simulation models to forecast dry-gas production under several production scenarios in the Chuchupa field. We selected eight geologic interpretations, representing the range of original gas in place (OGIP) and reservoir geometries determined in the static modeling, to perform dynamic history matches. The OGIP range of the models with very good history matches corresponds closely to the P10 to P90 OGIP range calculated from static modeling. In addition, we calibrated the various models with historical bottomhole and tubinghead flowing pressures and coupled the reservoir model with a network consisting of surface lines and equipment, pipelines from two platforms to the onshore sale-point station, and multistage compression to 1,215 psia. The set of probabilistic models is currently used to evaluate various production and market scenarios. Introduction Chuchupa field has produced 1.9 Tscf of dry gas, or approximately 40% of the OGIP. At the time of this study, three new horizontal wells were being planned, and new gas-sales agreements were being considered. Recent seismic reinterpretation, a new stratigraphic study, and a revision of the petrophysical model resulted in new probabilistic static models for the field. While these static models were being built, a parallel numerical-simulation study was conducted to determine the range of OGIP values that could be successfully history matched. Nine numerical reservoir models were generated by applying pore-volume multipliers to the prior-generation reservoir model, yielding a range of OGIP from 3.8 to 6.6 Tscf. We attempted to history match each of these nine models by using an optimization routine to adjust aquifer support, vertical transmissibility across a potential seal, and rock compressibility. The optimization routine proved to be a very useful and efficient tool to attain good-quality history matches in short periods of time. Good matches were obtained for models with OGIP ranging from 4.3 to 5.8 Tscf. On the basis of this information, the geologic modelers revised petrophysical parameters and generated 27 static models, encompassing three structural interpretations, three porosity distributions, and three possible positions of the gas/water contact (GWC). From experimental design, we obtained P10, P50, and P90values of 4.1, 4.7, and 5.3 Tscf, respectively. We scaled up and built reservoir-simulation models on eight of these models and performed history matches. The observed parameters to match were static well pressures and the absence of water production. Six of the eight models were satisfactorily history matched, with reasonable adjustments to aquifer strength, vertical transmissibility, and rock compressibility. The successfully history-matched models are within the P10 to P90 OGIP range. We selected three models to forecast future gas production. These models match the P10, P50, and P90 OGIP values determined in the probabilistic static model and combine the low, mid, and high structures, porosity and Swi distributions, and the range of GWC positions.

scholarly journals Injection-production optimization of carbonate reservoir based on an inter-well connectivity model

2021 ◽  
pp. 014459872199465
Author(s):  
Yuhui Zhou ◽  
Sheng Lei ◽  
Xuebiao Du ◽  
Shichang Ju ◽  
Wei Li
Keyword(s):  
History Matching ◽  
Water Injection ◽  
Field Application ◽  
Carbonate Reservoir ◽  
Production Optimization ◽  
Oil Field ◽  
Carbonate Reservoirs ◽  
Utilization Rate ◽  
Production Volume ◽  
Connectivity Model

Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.

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.

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.

Kinetics and physiological characteristics of autotrophic dentrification by denitrifying sulfur bacteria

2000 ◽  
Vol 42 (3-4) ◽  
pp. 59-68 ◽  
Author(s):  
S.-E. Oh ◽  
K.-S. Kim ◽  
H.-C. Choi ◽  
J. Cho ◽  
I.S. Kim
Keyword(s):  
Gas Production ◽  
Parameter Estimates ◽  
Production Volume ◽  
Autotrophic Denitrification ◽  
Nonlinear Regression Analysis ◽  
Monod Equation ◽  
Sulfur Bacteria ◽  
The Media ◽  
Parameter Values ◽  
Mixotrophic Conditions

To study the kinetics and physiology of autotrophic denitrifying sulfur bacteria, a steady-state anaerobic master culture reactor (MCR) was operated for over six months under a semi-continuous mode and nitrate limiting conditions using nutrient/mineral/buffer (NMB) medium containing thiosulfate and nitrate. Characteristics of the autotropic denitrifier were investigated through the cumulative gas production volume and rate, measured using an anaerobic respirometer, and through the nitrate, nitrite, and sulfate concentrations within the media. The bio-kinetic parameters were obtained based upon the Monod equation using mixed cultures in the MCR. Nonlinear regression analysis was employed using nitrate depletion and biomass production curves. Although this analysis did not yield exact biokinetic parameter estimates, the following ranges for the parameter values were obtained: μmax =0.12-0.2 hr-1; k=0.3-0.4 hr-1; Ks=3-10mg/L; YNO3=0.4-0.5mg Biomass/mg NO3--N. Inhibition of denitrification occurred when the concentrations of NO3--N, and SO42- reached about 660mg/L and 2,000mg/L, respectively. The autotrophic denitrifying sulfur bacteria were observed to be very sensitive to nitrite but relatively tolerant of nitrate, sulfate, and thiosulfate. Under mixotrophic conditions, denitrification by these bacteria occurred autotrophically; even with as high as 2 g COD, autotrophic denitrification was not significantly affected. The optimal pH and temperature for autotrophic denitrification was about 6.5–7.5 and 33–35 °C, respectively.

scholarly journals ANTHROPOGENIC INFLUENCE OF THE KOMSOMOLSK OIL AND GAS CONDENSATE FIELD ON MODERN DEFORMATION PROCESSES

2018 ◽  
pp. 11-20 ◽  
Author(s):  
Yu. V. Vasilev ◽  
D. A. Misyurev ◽  
A. V. Filatov
Keyword(s):  
Oil And Gas ◽  
Gas Production ◽  
Gas Condensate ◽  
Industrial Safety ◽  
Subsidence Trough ◽  
Oil And Gas Production ◽  
Field Development ◽  
Repeated Observations ◽  
Deformation Processes ◽  
The Relationship

The authors created a geodynamical polygon on the Komsomolsk oil and gas condensate field to ensure the industrial safety of oil and gas production facilities. The aim of its creation is mul-tiple repeated observations of recent deformation processes. Analysis and interpretation of the results of geodynamical monitoring which includes class II leveling, satellite observations, radar interferometry, exploitation parameters of field development provided an opportunity to identify that the conditions for the formation of recent deformations of the earth’s surface is an anthropogenic factor. The authors identified the relationship between the formation of subsidence trough of the earth’s surface in the eastern part of the field with the dynamics of accumulated gas sampling and the fall of reservoir pressures along the main reservoir PK1 (Cenomanian stage).

scholarly journals A practical method for planning large number of horizontal wells with a reservoir model for a field development plan

2021 ◽  
Vol 10 ◽  
pp. 17-32
Author(s):  
Guido Fava ◽  
Việt Anh Đinh
Keyword(s):  
Horizontal Well ◽  
Horizontal Wells ◽  
Simulation Software ◽  
Production Performance ◽  
Development Plan ◽  
Regular Pattern ◽  
Production Forecast ◽  
Advanced Technique ◽  
Large Reservoir ◽  
Field Development

The most advanced technique to evaluate different solutions proposed for a field development plan consists of building a numerical model to simulate the production performance of each alternative. Fields covering hundreds of square kilometres frequently require a large number of wells. There are studies and software concerning optimal planning of vertical wells for the development of a field. However, only few studies cover planning of a large number of horizontal wells seeking full population on a regular pattern. One of the criteria for horizontal well planning is selecting the well positions that have the best reservoir properties and certain standoffs from oil/water contact. The wells are then ranked according to their performances. Other criteria include the geometry and spacing of the wells. Placing hundreds of well individually according to these criteria is highly time consuming and can become impossible under time restraints. A method for planning a large number of horizontal wells in a regular pattern in a simulation model significantly reduces the time required for a reservoir production forecast using simulation software. The proposed method is implemented by a computer script and takes into account not only the aforementioned criteria, but also new well requirements concerning existing wells, development area boundaries, and reservoir geological structure features. Some of the conclusions drawn from a study on this method are (1) the new method saves a significant amount of working hours and avoids human errors, especially when many development scenarios need to be considered; (2) a large reservoir with hundreds of wells may have infinite possible solutions, and this approach has the aim of giving the most significant one; and (3) a horizontal well planning module would be a useful tool for commercial simulation software to ease engineers' tasks.

scholarly journals Research on Gas-liquid Mixed Transportation Technological Adaptability: A Case Study of the Western Sichuan Gas Field

2017 ◽  
Vol 10 (1) ◽  
pp. 37-47
Author(s):  
Qingsha Zhou ◽  
Kun Huang ◽  
Yongchun Zhou
Keyword(s):  
Flow Simulation ◽  
Field Tests ◽  
Economic Benefits ◽  
Gas Production ◽  
Simulation Software ◽  
Rapid Decline ◽  
Gas Field ◽  
Western Sichuan ◽  
Field Development ◽  
Well Production

Background: The western Sichuan gas field belongs to the low-permeability, tight gas reservoirs, which are characterized by rapid decline in initial production of single-well production, short periods of stable production, and long periods of late-stage, low-pressure, low-yield production. Objective: It is necessary to continue pursuing the optimization of transportation processes. Method: This paper describes research on mixed transportation based on simplified measurements with liquid-based technology and the simulation of multiphase processes using the PIPEPHASE multiphase flow simulation software to determine boundary values for the liquid carrying process. Conclusion: The simulation produced several different recommendations for the production and maximum multiphase distance along with difference in elevation. Field tests were then conducted to determine the suitability of mixed transportation in western Sichuan, so as to ensure smooth progress with fluid metering, optimize the gathering process in order to achieve stable and efficient gas production, and improve the economic benefits of gas field development.

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