knowledge Objective Questionnaire

Sample elements of Process Risks , Pain points at processes, knowledge objective questionnaires

Sr no	Risk group	Risk component	Assessment features	Severity of risk	Chance of occurrence	Ease of risk detection	LSS process practice scope
1	Risk scope associated with material procurements, supply chain	Supplier failing to supply materials causing work stoppage	Unproductive waiting time, a kind of waste	high	medium	Low
		Faulty material supply endangering project quality	Hidden loss by threatened project failure owing to faulty material	high	medium	Low
		High rate of material rejection causing great delays	Waste by material defect.	medium	medium	high
		Legal conflicts hampering flow of work	Time waste from conflicts hampering progress of work	high	low	Low

Sr no	Risk group	Risk component	Assessment features	Severity of risk	Chance of occurrence	Ease of detection	LSS process practice scope
1	Risk scope associated with financial handling process, invoice handling	Disagreements and conflicts leading to court cases and time waste leading to projects held up	Time waste	high	medium	low
		Piling up of great many jobs as back log not possible to handle by limited manpower	Accumulated inventory of pending work- long waiting time – a kind of waste	high	high	low
	Risk scope associated with stores and inventory handling process	Amount of shipment far exceeds the capacity of the inventory, owing to poor planning	Over-production type of waste with effect in increased cost	high	medium	low
		Great delays in identifying and release of materials owing to improper inventory system, affecting the projects and operations	Time waste owing to improper system	medium	medium	Medium

Sr no	Risk group	Risk component	Assessment features	Severity of risk	Chance of occurrence	Ease of risk detection	LSS process practice scope
1	Risk scope associated with development drilling design process	Unfer-designed drilling specifications leading to impractical point of drilling further with current limited provision- loss of time as new scope needs whole cycle of approval	Waste of time by defective action.	high	low	medium
		Overdesigned drilling specifications leading to excessive cost drilling wells and unnecessary capital locking	Waste of money is threatened if followed. Wasted effort in the design laden with defect.	medium	medium	low
		Inaccurate projection of depth versus formation profile makes erroneous design specifications	Defective design could lead to loss. Wasted effort in the design laden with defect.	high	medium	low
		Lot of uncertainties in drilling wells in unknown new area, with possible unforeseen problems	At least the cost should be controlled against uncertain result.	high	high	low
		Significant changes in the scope of work by the requesting department after material procurement done, thereby threatening long delays and additional cost commitments and unused inventory of many items.	Wasted design effort owing to no proactive precaution and control. More care in upstream plan was needed.	medium	high	medium

Sr no	Risk group	Risk component	Assessment features	Severity of risk	Chance of occurrence	Ease of risk detection	LSS process practice scope
5	Risk scope associated with Well completion process	Poor cementation jobs and zone isolation failure, thereby jeopardising the completion plan, while rig is waiting with daily rental cost	Time and money waste, unless minimizing the chance by standard practice enforcement	high	medium	medium
		Perforation shots failing to produce permeable conduits. Clogged perforation	Time and money waste. Needs to be minimised.	high	medium	medium
		Packer isolation failure between zones	Time and money waste, unless prevented by standard procedure enforcement.	high	medium	medium

Process	Pain point
Fields development planning	Big plan with scanty data, stressful situation for committing big investment	Inadequate level of data for firm plan	Apply collective wisdom at this stage of inadequate data. Study studies for help	Lean VSM, Kaizen
	Reservoir uncertainty even after data acquisition does not improve for confidence to investment commitment	Uncertainties in the nature of reservoir characteristics	Apply collective wisdom and consult global cases for help	DMAIC
	Process of integrated information generation involving multiple disciplines is quite slow	Lack of expertise in using the information system aptly	Train people about the available systems to improve the situation	Lean HRD promotion
	Lack of approved fund is causing delay in pursuing an expensive drilling scheme	Approval delay	Provide supporting information note worthy to ease the process of approval	Lean VSM, Kaizen
	Lack of skilled manpower	Skilled Man power shortage	Make manpower requisition and coordinate with recruitment dept	Lean VSM, Kaizen

Process	Pain point
Reservoir characterization	There are errors in data thereby increasing work load to first fix the integrity of data	Data errors are increasing work load from defects	Apply a system that tracks errors quickly	Lean TIMWOOD, Kaizen
	Lack of adequate data distribution is causing concern in reservoir characterization	Inadequate distribution of data by depth and or area	Make plan for collection of additional data that gives better representation of data distribution	Lean Kaizen,
	Lack of provision for special core analysis is causing concern for higher cost of testing	High cost of Special core analysis by external parties is a kind of waste where inhouse provision can be made by some investment plan for inhouse laboratory facility in view of many more lab experiments	Make plan for inhouse laboratory facility for SCAL studies	Standard Project
	Some correlations are questionable, owing to lack of adequate data	Inadequate data for some critical sections	Make plan for data acquisitions for the specific location and depth	Lean Kaizen
	New surveillance plan is not ideally aligned to data needs owing to cost cut has trimmed the surveillance plan	Improper surveillance plan	Make improved surveillance plan	Lean Kaizen

Process	Pain point	Causes	Changes required	Project level
Budget management Capex	Full information is not available	Required information sometimes missing in budget proposal of job requesting department	Different relevant depts are to work closely for proper communication	Kaizen
	Different departments to which others are dependent for budgeting should trigger budget initiative in time	Requesting department is delaying its budget proposal	Better coordination required between concerned departments	DMAIC
	System does not have accurate up to date figures	System is not up to date figures	Data owning dept to provide all required data into the system	Kaizen to improve for data gap filling
Budget management- OPEX	Some need to ask again to job requesting dept for specific information	Full information is not always given by job requesting dept	Relevant depts to work closely to ensure all required information is presented	DMAIC
Budget management	No easy access to contract data and contract prices	Budget unit does not have easy access to contracts	Hard copy of contract to be sent to all relevant parties	KAIZEN

process	Pain point	causes	Changes required
Contract management- performance monitoring	Current penalty clauses are not easy to implement	Difficulty in implementing some clause of penalty	Provide incentives in terms of improved future contract considerations. Link penalty clauses to KPI.	Lean Kaizen
Contract management- contract pre-qualification	Pre-qualification process takes too much time in case of urgent work	LENGTHY APPROVAL EVALUATION.	Use collaboration with appropriate parties to identify relevant service providers.	Lean Kaizen
Contract adjustment order	Too many changes causing delay	Too many change requests	Joint meeting between relevant depts needed to get the realistic picture of capacity handling	Lean Kaizen

Questionnaire sets oil/gas technical

1. An unconsolidated but clean sandstone at shallow depth is expected to havePoor permeabilitySomewhat higher permeabilityPermeability can not be determined in any case

2. There can be some correlation established between porosity and permeabilityYesNo

3. Underground oil reserve expressed at standard surface condition is computed byArea, net pay thickness, porosity, oil saturationArea, net pay thickness, porosity , oil saturation, FVFArea, gross layer thickness, porosity , oil saturation, FVFArea ,net pay thickness, oil saturation, permeability x FVFNeither of the above

4. Oil reserve at underground condition issame as in surface standard conditionReserve at surface standard condition * formation volume factorReserve at surface standard condition / formation volume factorNone of the above

5. An undersaturated reservoir is expected to haveBubble point pressure always equal to static reservoir pressureBubble point pressure less than static reservoir pressureBubble point pressure greater than static reservoir pressureBubble point pressure always equal to flowing reservoir pressureBubble point pressure does not exist

6. An oil bearing reservoir surrounded by active aquifer is expected to haveNo impact from aquifer for ultimate oil recoveryUltimate oil recovery would be lower than if no aquiferUltimate oil recovery would be higher than if no aquiferThe wells from the reservoir will produce no oil

7. An oil reservoir with gas dissolved in it willFirst produce only gas and then oil at gather centreFirst produce only oil then gas at gathering centreWith produce oil and gas together at gathering centre

8. An oil reserve with quite low GOR on production is expected to havewill have slower pressure decline in the reservoirwill have faster pressure decline in the reservoirpressure decline will be similar to one with high gor

1. HistogramX axis category data and y axis category dataX axis category data and y axis count dataX axis count data and y axis continuous dataX axis count data and y axis count dataNone of the aboveThe two axes of histogram can have

2. Box plotmode data organizationmean data organizationmedian data organizationNone of the aboveA box plot is based on

6. Skewed distributionIs at the centre of the graphTowards left of the graph onlyTowards right of the graph onlyTowards left or right of the graphNone of the aboveIn a skewed data distribution, the mean value

9.Comparative box plotDifferent samples of data are represented in box plotThe box plot ranges may overlap each other in some caseSome box plot range may not overlap with any other in some caseA and b onlyA , b and cIn comparative boxplot

10. Continuous dataInterpolation between values makes senseInterpolation between values does not make senseCan have decimal numbersA and CB and CA continuous data set

11. Discrete type dataContinuous type of dataDiscrete type of dataDecimal numberCategory dataNone of the aboveWe tried to count the number of time some events occur at different time intervals. The counted numbers are

12 . Categorical data

13 . Attributes

14 . Central theoremIt is a theorem in the field of economicsIt is a theorem in the field of arithmeticIt is a theorem in the field of lawIt is a theorem in the field of statistics

15 .Sample data analysisTakes entire population data into accountTakes just one data element from the populationTakes a small section of data elements randomly from total populationAll the aboveNone of the above