The Geochemical Survey Methods for Optimization of Oil Field Development

2021 ◽  
Author(s):  
Maria Sergeevna Shipaeva ◽  
Danis Karlovich Nurgaliev ◽  
Vladislav Anatolevich Sudakov ◽  
Artur Albertovich Shakirov ◽  
Azat Abuzarovich Lutfullin ◽  
...  
Keyword(s):  
Flow Rate ◽  
Reservoir Simulation ◽  
Produced Water ◽  
Survey Methods ◽  
Simulation Models ◽  
Oil Field ◽  
Geochemical Composition ◽  
Field Development ◽  
Water Composition ◽  
The Impact

Abstract The paper considers issues of determining the direction of filtration for oil deposits by means of complex study of the geochemical composition of formation fluids and the dynamics of bottomhole pressure and flow rates, and further use of this information in geological and reservoir simulation models. This integrated technology is not expensive and makes it possible to identify geological uncertainties in the reservoir for intelligent management of development processes, such as waterflooding optimization, reservoir simulation models improvement, water cut source definition, etc. Improving the reliability of information about the reservoir and the presented fluids is undoubtedly relevant and significant task. To solve this problem, fluid samples were taken and complex studies of the composition of the produced water was carried out, including the determination of hydrogen and oxygen isotopes and element composition. The authors note that the isotopic composition of formation waters for a number of wells differs from the analogical parameters for injected water, which is probably associated with the area of ​​uneven reservoir distribution and the existence of a stagnant undrained zone. The result of the calculations is an estimate of the impact coefficient of the injected water on the water composition in the surrounding producer wells. In addition to this, the work included the analysis of the dynamics of fluid flow rate, oil flow rate, bottomhole and reservoir pressures, the influence of injection on the pressure in the drainage area of ​​producer wells. Basing on the results obtained the recommendations were given for changing the injection patterns as it is noted that a number of wells are not affected by injection. Recommendations have been developed for carrying out workovers in order to prevent a decrease in pressure and an increase in oil production.

Simultaneous Measuring Method for Both Volumetric Flow Rates of Air-Water Mixture Using a Turbine Flowmeter

1996 ◽  
Vol 118 (1) ◽  
pp. 29-35 ◽  
Author(s):  
K. Minemura ◽  
K. Egashira ◽  
K. Ihara ◽  
H. Furuta ◽  
K. Yamamoto
Keyword(s):  
Pressure Drop ◽  
Flow Rate ◽  
Volumetric Flow Rate ◽  
Oil Field ◽  
Liquid Density ◽  
Water Mixture ◽  
Rotor Speed ◽  
Flow Rates ◽  
Field Development ◽  
Turbine Flowmeter

A turbine flowmeter is employed in this study in connection with offshore oil field development, in order to measure simultaneously both the volumetric flow rates of air-water two-phase mixture. Though a conventional turbine flowmeter is generally used to measure the single-phase volumetric flow rate by obtaining the rotational rotor speed, the method proposed additionally reads the pressure drop across the meter. After the pressure drop and rotor speed measured are correlated as functions of the volumetric flow ratio of the air to the whole fluid and the total volumetric flow rate, both the flow rates are iteratively evaluated with the functions on the premise that the liquid density is known. The evaluated flow rates are confirmed to have adequate accuracy, and thus the applicability of the method to oil fields.

Diagnostic Plots for Production Decline During the Transition of Oil Field Development From Depletion to Water Injection

2021 ◽  
Author(s):  
Vil Syrtlanov ◽  
Yury Golovatskiy ◽  
Ivan Ishimov
Keyword(s):  
Water Injection ◽  
Simulation Models ◽  
Oil Field ◽  
Production Data ◽  
Oil Reservoir ◽  
Field Development ◽  
Well Production ◽  
Diagnostic Plots ◽  
Oil Field Development ◽  
Analytical Approaches

Abstract In this paper the simplified way is proposed for predicting the dynamics of liquid production and estimating the parameters of the oil reservoir using diagnostic curves, which are a generalization of analytical approaches, partially compared with the results of calculations on 3D simulation models and with actual well production data.

Incorporating Economic Decisions into Reservoir Simulation to Support Accurate and Efficient Optimization and Analysis of Field Development Strategies

2021 ◽  
Author(s):  
Jim Browning ◽  
Sheldon Gorell
Keyword(s):  
Reservoir Simulation ◽  
Value Added ◽  
Simulation Models ◽  
Operating Conditions ◽  
Conditional Logic ◽  
Economic Optimization ◽  
Field Development ◽  
Production Constraints ◽  
Automated Method ◽  
Economic Decision Making

Abstract Economic optimization of a reservoir can be extremely tedious and time consuming. It is particularly difficult with many wells, some of which can become non-economic within the simulated time period. These problems can be mitigated by: 1) analyzing the results of a simulation once it has run, or 2) applying injection or production constraints at the well level. An example of option 1 would be integration with a spreadsheet or economic simulation package after the simulation has run. An example of option 2 would be to set a maximum water cut, upon which the well constraints could be changed, or the well could be shut in within the simulation. Both of these methods have drawbacks. If the goal is to account for how changes in a well operating strategy affects other wells, then analysis after the fact requires many runs to sequentially identify and modify well constraints at the correct times and in the correct order. In contrast, applying injection and production constraints to wells is not the same as applying true economic constraints. The objective of this work was to develop an automated method which includes economic considerations within the simulator to decrease the amount of time optimizing a single model and allows more time to analyze uncertainty within the economic decision making process. This study developed automated methods and procedures to include economic calculations within the context of a standard reservoir simulation. The method utilized modifications to available conditional logic features to internally include and export key economic metrics to support appropriate automatic field development changes. This method was tested using synthetic models with different amounts of wells and operating conditions. It was validated using after the fact calculations on a well by well basis to confirm the process. People costs are always among the most significant associated with running a business. Therefore, it is imperative for people to be as efficient and productive as possible. The method presented in this study significantly reduces the amount of time and effort associated with tedious and manual manipulations of simulation models. These savings enable an organization to focus on more value-added activities including, but not limited to, accurately optimizing and estimating of uncertainty associated decisions supported by reservoir simulation.

scholarly journals The impact of bacterial diversity on resistance to biocides in oilfields

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gabriela Feix Pereira ◽  
Harry Luiz Pilz-Junior ◽  
Gertrudes Corção
Keyword(s):  
Water Samples ◽  
Produced Water ◽  
Functional Characterization ◽  
Amplicon Sequencing ◽  
Oil Field ◽  
Oil Fields ◽  
Sulfate Reducing ◽  
16S Rrna Amplicon Sequencing ◽  
Dimethyl Benzyl ◽  
The Impact

AbstractExtreme conditions and the availability of determinate substrates in oil fields promote the growth of a specific microbiome. Sulfate-reducing bacteria (SRB) and acid-producing bacteria (APB) are usually found in these places and can harm important processes due to increases in corrosion rates, biofouling and reservoir biosouring. Biocides such as glutaraldehyde, dibromo-nitrilopropionamide (DBNPA), tetrakis (hydroxymethyl) phosphonium sulfate (THPS) and alkyl dimethyl benzyl ammonium chloride (ADBAC) are commonly used in oil fields to mitigate uncontrolled microbial growth. The aim of this work was to evaluate the differences among microbiome compositions and their resistance to standard biocides in four different Brazilian produced water samples, two from a Southeast Brazil offshore oil field and two from different Northeast Brazil onshore oil fields. Microbiome evaluations were carried out through 16S rRNA amplicon sequencing. To evaluate the biocidal resistance, the Minimum Inhibitory Concentration (MIC) of the standard biocides were analyzed using enriched consortia of SRB and APB from the produced water samples. The data showed important differences in terms of taxonomy but similar functional characterization, indicating the high diversity of the microbiomes. The APB and SRB consortia demonstrated varying resistance levels against the biocides. These results will help to customize biocidal treatments in oil fields.

Optimising Oil Field Net Present Value with Produced Water Salinities and Tracers

2021 ◽  
Author(s):  
Babalola Daramola
Keyword(s):  
Reservoir Simulation ◽  
Produced Water ◽  
Water Injection ◽  
Oil Production ◽  
Oil Field ◽  
Water Flooding ◽  
Water Salinity ◽  
History Match ◽  
Infill Drilling ◽  
Salinity Data

Abstract This paper presents case studies of how produced water salinity data was used to transform the performance of two oil producing fields in Nigeria. Produced water salinity data was used to improve Field B’s reservoir simulation history match, generate infill drilling targets, and reinstate Field C’s oil production. A reservoir simulation study was unable to history match the water cut in 3 production wells in Field B. Water salinity data enabled the asset team to estimate the arrival time of injected sea water at each production well in oil field B. This improved the reservoir simulation history match, increased model confidence, and validated the simulation model for the placement of infill drilling targets. The asset team also gained additional insight on the existing water flood performance, transformed the water flooding strategy, and added 9.6 MMSTB oil reserves. The asset team at Field C was unable to recover oil production from a well after it died suddenly. The team evaluated water salinity data, which suggested scale build up in the well, and completed a bottom-hole camera survey to prove the diagnosis. This justified a scale clean-out workover, and added 5000 barrels per day of oil production. A case study of how injection tracer data was used to characterise a water injection short circuit in Field D is also presented. Methods of using produced water salinity and injection tracer data to manage base production and add significant value to petroleum fields are presented. Produced water salinity and injection tracer data also simplify water injection connectivity evaluations, and can be used to justify test pipeline and test separator installation for data acquisition.

scholarly journals Refining Permeability Values for History-Matching of the Reservoir Simulation Model

2020 ◽  
Vol 20 (3) ◽  
pp. 223-230
Author(s):  
Margarita A. Smetkina ◽  
◽  
Oleg A. Melkishev ◽  
Maksim A. Prisyazhnyuk ◽  
◽  
...  
Keyword(s):  
Reservoir Simulation ◽  
History Matching ◽  
Simulation Models ◽  
Data Interpretation ◽  
Well Logging ◽  
Initial Permeability ◽  
Oil Field ◽  
Statistical Characteristics ◽  
Reservoir Model ◽  
Porosity And Permeability

Reservoir simulation models are used to design oil field developments, estimate efficiency of geological and engineering operations and perform prediction calculations of long-term development performances. A method has been developed to adjust the permeability cube values during reservoir model history-matching subject to the corederived dependence between rock petrophysical properties. The method was implemented using an example of the Bobrikovian formation (terrigenous reservoir) deposit of a field in the Solikamskian depression. A statistical analysis of the Bobrikovian formation porosity and permeability properties was conducted following the well logging results interpretation and reservoir modelling data. We analysed differences between the initial permeability obtained after upscaling the geological model and permeability obtained after the reservoir model history-matching. The analysis revealed divergences between the statistical characteristics of the permeability values based on the well logging data interpretation and the reservoir model, as well as substantial differences between the adjusted and initial permeability cubes. It was established that the initial permeability was significantly modified by manual adjustments in the process of history-matching. Extreme permeability values were defined and corrected based on the core-derived petrophysical dependence KPR = f(KP) , subject to ranges of porosity and permeability ratios. By using the modified permeability cube, calculations were performed to reproduce the formation production history. According to the calculation results, we achieved convergence with the actual data, while deviations were in line with the accuracy requirements to the model history-matching. Thus, this method of the permeability cube adjustment following the manual history-matching will save from the gross overestimation or underestimation of permeability in reservoir model cells.

scholarly journals Influence of well management in the development of multiple reservoir sharing production facilities

2020 ◽  
Vol 75 ◽  
pp. 70
Author(s):  
João Carlos von Hohendorff Filho ◽  
Denis José Schiozer
Keyword(s):  
Oil Recovery ◽  
Development Project ◽  
Gas Production ◽  
Oil Field ◽  
The Other ◽  
Dynamic Flow ◽  
Field Development ◽  
Light Oil ◽  
Multiple Reservoir ◽  
The Impact

Well prioritization rules on integrated production models are required for the interaction between reservoirs and restricted production systems, thus predicting the behavior of multiple reservoir sharing facilities. This study verified the impact of well management with an economic evaluation based on the distinct prioritizations by reservoir with different fluids. We described the impact of the well management method in a field development project using a consolidated methodology for production strategy optimization. We used a benchmark case based on two offshore fields, a light oil carbonate and a black-oil sandstone, with gas production constraint in the platform. The independent reservoir models were tested on three different approaches for platform production sharing: (Approach 1) fixed apportionment of platform production and injection, (Approach 2) dynamic flow-based apportionment, and (Approach 3) dynamic flow-based apportionment, including economic differences using weights for each reservoir. Approach 1 provided the intermediate NPV compared with the other approaches. On the other hand, it provided the lowest oil recovery. We observed that the exclusion of several wells in the light oil field led to a good valuation of the project, despite these wells producing a fluid with higher value. Approach 2 provided the lower NPV performance and intermediate oil recovery. We found that the well prioritization based on flow failed to capture the effects related to the different valuation of the fluids produced by the two reservoirs. Approach 3, which handled the type of fluids similarly to Approach 1, provided a greater NPV and oil recovery than the other approaches. The weight for each reservoir applied to well prioritization better captured the gains related to different valuation of the fluids produced by the two reservoirs. Dynamic prioritization with weights performed better results than fixed apportionment to shared platform capacities. We obtained different improvements in the project development optimization due to the anticipation of financial returns and CAPEX changes, due mainly from adequate well apportionment by different management algorithm. Well management algorithms implemented in traditional simulators are not developed to prioritize different reservoir wells separately, especially if there are different economic conditions exemplified here by a different valuation of produced fluids. This valuation should be taken into account in the short term optimization for wells.

scholarly journals ANALYSIS OF THE TRACER STUDIES RESULTS: A STUDY OF AS1-3 FORMATION OF THE SEVERO-OREKHOVSKOYE OIL FIELD

2018 ◽  
pp. 44-51
Author(s):  
V. F. Dyagilev ◽  
S. T. Polischuk ◽  
S. A. Leontev ◽  
V. M. Spasibov
Keyword(s):  
Mathematical Analysis ◽  
Analysis Data ◽  
Oil Field ◽  
Tracer Studies ◽  
Injection Wells ◽  
Field Development ◽  
Field Practice ◽  
Production Wells ◽  
The Impact ◽  
State Of Field

In oil field practice tracer (indicator) studies are an effective and efficient method of monitoring the state of field development. Using the multifactor mathematical analysis, the nature and intensity of the impact of injection wells on production wells have been compared with the results of injection of indicator liquids. Injection of indicator liquids was carried out along the AS1-3 formation at the Severo-Orekhovskoye oil field through the wellheads of the injection wells. The technique provides for correlation of injection in all potentially possible directions within a given range of action (usually no more than 2 rows), excluding one or more of the wells and more from the analysis. There is a direct positive correlation between evaluation data on indicator downloads and multivariate mathematical analysis data. The convergence of the results is 65%.

Sign in / Sign up

Export Citation Format

Share Document