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Cross-domain data analysis is arguably the most important part of oilfield data analytics. While it enables holistic process optimization, it is also challenging to execute. Data are often scattered across different databases making it complex to join and may require multidomain expertise to properly analyze. Here, processing and analysis of data collected by three well construction business lines of the same service company were performed to establish a link between drilling fluid properties and drilling performance. The data engineering workflow starts by taking information from a single service company and combining that information about drilling operations, drill bits, and drilling fluids into a single dataset. Metadata including locations, operators, and wells are then mapped, and overlapping attributes are unified and reconciled. Data is further processed to extract relevant drilling performance metrics and drilling fluid properties and then labeled by well, section, and drilling run. The resultant data workflow enables detailed analysis, focusing on particular locations, drilling practices, hole conditions, and fluids. The joined, cleaned, and processed dataset includes information from thousands of wells drilled globally since 2016. The datasets from different sources differ in the level of detail, but are complementary to each other, providing a broader picture when merged. The data is organized and visualized on dashboards, enabling in-depth analysis through intuitive filtering on a variety of conditions. These conditions may include location, drilling run type, depth, used drill bits and tools, and drilling fluid type and properties. The main drilling performance metrics are distance drilled per run and run duration. These are used to calculate the run average rate of penetration (ROP). Reasons for pulling out of the hole (POOH) and risks for POOH are extracted from text comments of the daily drilling reports. This enables the tracking of abnormal run terminations due to drilling tool failures. It also enables tracking of wellbore integrity, and substandard drilling and hole conditioning practices, especially at section total depth (TD) or because of drilling fluid issues. Aggregated metrics of minimum, maximum, and median are used for high-level data evaluation. Statistical significance of effects and causality are analyzed in detail on selected cases. Based on the data, several examples of such analyses are created that focus on the effects of water-based fluid vs. oil-based fluid, on drilling performance in the major oil fields in the United States. Holistic analysis of the effects of drilling fluids on drilling performance becomes possible through the well construction cross-domain data fusion. The developed workflow enables analysis of drilling fluid-related big data, covering tens of thousands of wells globally. The analysis results are expected to improve drilling efficiency and reliability and ultimately reduce operators' total well expenditures.
Cross-domain data analysis is arguably the most important part of oilfield data analytics. While it enables holistic process optimization, it is also challenging to execute. Data are often scattered across different databases making it complex to join and may require multidomain expertise to properly analyze. Here, processing and analysis of data collected by three well construction business lines of the same service company were performed to establish a link between drilling fluid properties and drilling performance. The data engineering workflow starts by taking information from a single service company and combining that information about drilling operations, drill bits, and drilling fluids into a single dataset. Metadata including locations, operators, and wells are then mapped, and overlapping attributes are unified and reconciled. Data is further processed to extract relevant drilling performance metrics and drilling fluid properties and then labeled by well, section, and drilling run. The resultant data workflow enables detailed analysis, focusing on particular locations, drilling practices, hole conditions, and fluids. The joined, cleaned, and processed dataset includes information from thousands of wells drilled globally since 2016. The datasets from different sources differ in the level of detail, but are complementary to each other, providing a broader picture when merged. The data is organized and visualized on dashboards, enabling in-depth analysis through intuitive filtering on a variety of conditions. These conditions may include location, drilling run type, depth, used drill bits and tools, and drilling fluid type and properties. The main drilling performance metrics are distance drilled per run and run duration. These are used to calculate the run average rate of penetration (ROP). Reasons for pulling out of the hole (POOH) and risks for POOH are extracted from text comments of the daily drilling reports. This enables the tracking of abnormal run terminations due to drilling tool failures. It also enables tracking of wellbore integrity, and substandard drilling and hole conditioning practices, especially at section total depth (TD) or because of drilling fluid issues. Aggregated metrics of minimum, maximum, and median are used for high-level data evaluation. Statistical significance of effects and causality are analyzed in detail on selected cases. Based on the data, several examples of such analyses are created that focus on the effects of water-based fluid vs. oil-based fluid, on drilling performance in the major oil fields in the United States. Holistic analysis of the effects of drilling fluids on drilling performance becomes possible through the well construction cross-domain data fusion. The developed workflow enables analysis of drilling fluid-related big data, covering tens of thousands of wells globally. The analysis results are expected to improve drilling efficiency and reliability and ultimately reduce operators' total well expenditures.
Drilling wells with water-based fluid systems can be problematic due to the water reactivity of clay-containing shale minerals. This fundamental issue is the most often cited performance gap between non-aqueous fluid (NAF) and water-based fluids (WBF). The consequences of uncontrolled shale hydration include issues such as bit-balling/accretion, reduced ROP, wellbore collapse, and overall increased wellbore construction costs. This problem is typically addressed by the addition of shale inhibitors which can span multiple types of chemistries. The maintenance of these additives is nuanced due to their inherent depletion on reactive minerals leading to uncertainty of active concentration of these additives during a drilling campaign. Considering the critical need to maintain concentrations of these additives, uncertainty is not an optimal plan to ensure success. To this end, we have designed quantitative shale inhibitor tracking technology to measure amine-based shale inhibitors in high-performance water-based fluids. The method is robust, detects only amine-based swelling inhibitors, and is fully amenable to be performed at a rig site. We developed a colorimetric assay that quantitatively measures amine-based shale inhibitors in filtrates of WBFs. The reaction to generate color utilizes proprietary reagents that selectively target only the amines of interest, and is not influenced by nitrogen-containing polymers such as polyacrylamides. Additionally, the results of the test are not influenced by any common drilling fluid additives, including black powders. The colored solutions produced in the test are measured by advanced spectroscopic analysis with a handheld, portable field meter at a specific wavelength. The absorbance is used to determine the concentration of the amine inhibitor in the fluid filtrate. Finally, we have tested reliability of the method through numerous approaches including Gage Repeatability and Reproducibility statistical analysis. With this new technology, we have explored amine depletion on reactive clays in a lab setting, uncovering unique depletion rates based on amine chemistry. Additionally, we have trialed this technology in multiple wells. We have validated the test method and equipment to be field friendly and accurate, as designed. Our field engineers have included this new measurement alongside a typical mud check. In our validation trials we have already observed different depletion rates based on well and operational procedures for amine inhibitor maintenance, and conflicting values of measured concentrations and product concentration estimates based on calculations. We have coupled high-performance fluid design with shale inhibitor tracking technology to reduce the uncertainty of WBF chemical composition. This technology will allow us to sustain effective concentrations of high-performance additives and improve operational reliability throughout the wellbore construction process. Furthermore, this technology will allow more effective re-use of WBF, reducing the environmental impact of our fluids, and lowering well costs.
Summary The Permian Basin, located in southeastern New Mexico and west Texas, is treated as the largest province of oil and gas production in the United States (US). The majority of hydrocarbon production from the Permian Basin is from the Wolfcamp shaly formation. Drilling horizontal and extended reached wells is continuously increasing day after day in the Permian Basin. Oil-based mud (OBM) is used to drill these horizontal wells for enhancing shale inhibition, reducing torque and drag, and supporting thermal stability of mud rheology. Due to environmental regulation for limiting use of OBM, the petroleum industry has tried to develop water-based fluid (WBF) that approaches the performance advantages of OBM. The main objective of this research is to formulate and develop WBF by using polyacrylamide anionic friction reducer (AFR) for drilling the lateral sections of horizontal wells in the shaly Wolfcamp formation. Shale inhibition, barite sagging, lubricity, and thermal stability of the formulated WBF with AFR will be studied to evaluate the developed WBF. Laboratory experiments were conducted to develop and evaluate the performance of the formulated WBF with AFR. The shale inhibition capabilities of the developed WBF with AFR were evaluated by using zeta potential, shale dispersion test, and immersion test. The results prove the capability of the formulated WBF with AFR to prevent both shale swelling and shale dispersion. AFR limits water penetrations to shale through encapsulation. The mixing procedures of AFR with WBF affect both the thermal stability of mud rheology and shale inhibition. Adding AFR to WBF helps to suspend weighting materials and mitigate barite sag. Besides, AFR decreases torque and drag by decreasing the coefficient of friction (COF). Furthermore, AFR supports enhanced stability of mud rheology with time up to 14 days at temperatures up to 180°F. The formulated WBF with AFR can be used for enhancing shale inhibition, supporting thermal and time stability of fluid rheology, improving lubricity, and minimizing barite sagging for drilling shaly Wolfcamp formations. This study presents a promising WBF to replace OBM to drill lateral sections in the Permian Basin.
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