Performance of cocoa beans production modelling in Indonesia

Cocoa beans production Indonesia has decline in recent years but demand for cocoa beans relatively increase. This research aims to analyse the modelling of cocoa beans production in Indonesia. This research used secondary data from 2005-2018, with simultaneous equation models. The results of this research indicate that the production of cocoa beans has a positive relationship with land area, international price of cocoa beans and lag of cocoa beans production, while the price of domestic cocoa beans has a negative relationship with cocoa beans production. Domestic demand for cocoa beans has a positive relationship with domestic price of cocoa beans and the cocoa processing industry. Domestic price of cocoa beans has a positive relationship with domestic demand for cocoa beans, international price of cocoa beans and lag domestic price of cocoa beans, while cocoa beans production has a negative relationship with domestic cocoa bean prices.

Application of Machine Learning Algorithms and Integrated Production Modelling to Improve Accuracy of Liquid Production Rate Measurements Using Multiphase Flow Meters

Objectives/Scope: During the period of two years the difference between sum of daily oil flow rate measurements of each oil production well using multiphase flow meter (MPFM) and cumulative daily oil production rate measured by custody transfer meter increased overall by 5%. For some wells inaccuracy of MPFM liquid rate measurement could reach 30-50%. The main goal of this research was to improve the accuracy of multiphase flow meter production rate measurements. Methods, Procedures, Process: More than 80 oil production wells were involved in the research, more than 100 flow rate tests were carried out. Machine learning methods such as supervised learning algorithms (linear and nonlinear regressions, method of gradient descent, finite differences algorithm, etc.) have been applied coupled with Integrated production modelling tools such as PROSPER and OpenServer in order to develop a function representing correlation between MPFM parameters and flow rate error. Results, Observations, Conclusions: The difference between cumulative daily oil production rate measured by custody transfer meter and multiphase flow meters decreased to 0.5%. The solution has been officially applied at the oil field and saved USD 500K to the Company. The reliability of the function was then proved by the vendor of MPFMs. Novel/Additive Information: For the first time machine learning algorithms coupled with Integrated Production modelling tools have been used to improve the accuracy of multiphase flow meter production rate measurements.

Lessons Learnt from Integrated Production Modelling and Performance Analysis of Gas Lift Wells of One of the Biggest Offshore Complexes in India

The paper aims to discuss various issues pertaining to gas lift system and instabilities in low producer wells along with the necessary measures for addressing those issues. The effect of various parameters such as tubing size, gas injection rate, multi-porting and gas lift valve port diameter on the performance analysis of integrated gas lift system along with the flow stability have been discussed in the paper. Field X is one of the matured offshore fields in India which has been producing for over 40 years. It is a multi-pay, heterogeneous and complex reservoir. The field is producing through six Process Complexes and more than 90% of the wells are operating on gas lift. As most of the producing wells in the field are operating on gas lift, continuous performance analysis of gas lift to optimize production is imperative to enhance or sustain production. 121 Oil wells and 7 Gas wells are producing through 18 Wellhead platforms to complex X1 of the field X. Out of these 121 oil wells, 5 are producing on self and remaining 116 with gas lift. In this paper, performance analysis of these 116 flowing gas lift wells, carried out to identify various problems which leads to sub-optimal production such as inadequate gas injection, multi-porting, CV choking, faulty GLVs etc. has been discussed. On the basis of simulation studies and analysis of findings, requisite optimization/ intervention measures proposed to improve performance of the wells have been brought out in the paper. The recommended measures predicted the liquid gain of about 1570 barrels per day (518 barrels of oil per day) and an injection gas savings in the region of about 28 million SCFD. Further, the nodal analysis carried out indicates that the aforementioned gas injection saving of 28 million SCFD would facilitate in minimizing the back pressure in the flow line network and is likely to result in an additional production gain of 350 barrels of liquid per day (65 barrels of oil per day) which adds up to a total gain of 1920 barrels of liquid per day (583 barrels of oil per day). Additionally, system/ nodal analysis has also been carried out for optimal gas allocation in the field through Integrated Production Modelling. The analysis brings out a reduction in gas injection by 46 million SCFD with likely incremental oil gain of ~100 barrels of oil per day.

Greenhouse gas emissions from livestock production: modelling methods, methane emission factors and mitigation strategies

This chapter discusses the systems analysis and life cycle assessment modelling approaches and also looks at a range of model applications. These applications include use within the national inventories of various countries across species including discussions around the use of different emission factors. The chapter concludes with applications to quantify emissions at the farm level and a discussion around some of the mitigation strategies that have been modelled previously.

From participatory engagement to co-production: Modelling climate-sensitive processes in the Arctic

Participation is increasingly being used in the modelling of climate-sensitive systems to improve usability. Bottom-up, place-based approaches to modelling can challenge the dominantly positivist approaches used until recently. We examined how participation is reported within modelling research that uses participatory approaches, focusing on the Arctic. Our systematic scoping review identified 26 articles that used participatory approaches in modelling research to explore a climate-sensitive process in an Arctic setting and analysed the degree of participation at each stage of the process for each article. A diversity of topics, modelling approaches, and participant groups were identified. Most studies (71%) occurred in the North American Arctic, and all studies engaged with non-Western knowledge types to some degree. Participation was most commonly reported at the model generation and participant identification stages, and least commonly reported in the choice of modelling type. Participatory scores—based upon the number and degree of participatory stages of a study—were higher where authors gave instrumental or transformative rationales for the use of participation, and among studies which described prioritising non-Western knowledge types. Detailed reporting of participatory processes was frequently absent, suggesting a need for clearer discussions of these issues in the descriptions of the process.